Automated mining involves the removal of human labor from the mining process. The mining industry is in the transition towards automation. It can still require a large amount of human capital, particularly in the developing world
where labor costs are low so there is less incentive for increasing
efficiency. There are two types of automated mining- process and
software automation, and the application of robotic technology to mining
vehicles and equipment.
Mine automation software
In
order to gain more control over their operations, mining companies may
implement mining automation software or processes. Reports generated by
mine automation software allow administrators to identify productivity
bottlenecks, increase accountability, and better understand return on investment.
Mining equipment automation
Addressing
concerns about how to improve productivity and safety in the mine site,
some mine companies are turning to equipment automation consisting of
robotic hardware and software technologies that convert vehicles or
equipment into autonomous mining units.
Mine equipment automation comes in four different forms: remote control, teleoperation, driver assist, and full automation.
Remote control
Remote control mining equipment usually refers to mining vehicles such as excavators or bulldozers
that are controlled with a handheld remote control. An operator stands
in line-of-sight and uses the remote control to perform the normal
vehicle functions. Because visibility and feel of the machine are
heavily reduced, vehicle productivity is generally reduced as well using
remote control. Remote control technology is generally used to enable
mining equipment to operate in dangerous conditions such as unstable
terrain, blast areas or in high risk areas of falling debris, or
underground mining. Remote control technology is generally the least
expensive way to automate mining equipment making it an ideal entry
point for companies looking to test the viability of robotic technology
in their mine.
Teleoperated mining equipment
Teleoperated
mining equipment refers to mining vehicles that are controlled by an
operator at a remote location with the use of cameras, sensors, and
possibly additional positioning software. Teleoperation
allows an operator to further remove themselves from the mining
location and control a vehicle from a more protected environment.
Joysticks or other handheld controls are still used to control the
vehicle's functions, and operators have greater access to vehicle
telemetry and positioning data through the teleoperation software. With
the operator removed from the cab, teleoperated mining vehicles may also
experience reduced productivity; however, the operator has a better
vantage point than remote control from on-vehicle cameras and sensors
and is further removed from potentially dangerous conditions.
Driver assist
"Driver
assist" refers to partly automated control of mining machines. Only
some of the functions are automated and operator intervention is needed.
Common functions include both spotting assist and collision avoidance systems.
Full automation
"Full
automation" can refer to the autonomous control of one or more mining
vehicles. Robotic components manage all critical vehicle functions
including ignition, steering, transmission, acceleration, braking, and
implement control (i.e. blade control, dump bed control, excavator
bucket and boom, etc.) without the need for operator intervention. Fully
autonomous mining systems experience the most productivity gains as
software controls one or more mining vehicles allowing operators to take
on the role of mining facilitators, troubleshooting errors and
monitoring efficiency.
Benefits
The
benefits of mining equipment automation technologies are varied but may
include: improved safety, better fuel efficiency, increased
productivity, reduced unscheduled maintenance, improved working
conditions, better vehicle utilization, and reduced driver fatigue and
attrition. Automation technologies are an efficient way to mitigate the
effects of widespread labor shortages for positions such as haul truck
driver. In the face of falling commodity prices, many mining companies
are looking for ways to dramatically reduce overhead costs while still
maintaining site safety and integrity; automation may be the answer.
Drawbacks
Critics
of vehicle automation often focus on the potential for robotic
technology to eliminate jobs while proponents counter that while some
jobs will become obsolete (normally the dirty, dangerous, or monotonous
jobs), others will be created. Communities supporting underprivileged
workers that rely on entry level mining positions are worried about and
are calling for social responsibility as mining companies transition to
automation technologies that promise to increase productivity in the
face of falling commodity prices. Risk averse mining companies
are also reluctant to commit large amounts of capital to an unproven
technology, preferring more often to enter the automation scene at
lower, more inexpensive levels such as remote control.
Examples of autonomous mining equipment
Mine of the future
Rio Tinto Group embarked on their Mine of the Future
initiative in 2008. From a control center in Perth, Rio Tinto employees
operate autonomous mining equipment in Australia's remote but mineral
rich Pilbara region. The autonomous mining vehicles reduce the footprint
of the mining giant while improving productivity and vehicle
utilization. As of June 2014,
Rio Tinto's autonomous mining fleet reached the milestone of 200
million tonnes hauled. Rio Tinto also operate a number of autonomous
blast hole drill rigs.
Bingham Canyon Mine
Located near Salt Lake City, Utah, the Bingham Canyon Mine (Kennecott Utah Copper/Rio
Tinto) is one of the largest open pit mine in the world and one of the
world's largest copper producers. In April 2013, the mine experienced a
catastrophic landslide that halted much of the mine's operations.
As part of the cleanup efforts and to improve safety, mine
administrators turned to remote control excavator, dozers and teleremote
blast hole drills to perform work on the highly unstable terrain areas.
Robotic technology helped Kennecott to reduce the steeper, more
dangerous areas of the slide to allow manned vehicles access for cleanup
efforts.
Automation of underground works in China
German
company «EEP Elektro-Elektronik Pranjic» delivered and put into
operation more than 60 sets of advanced automatic control for
underground coal mining for the period ~ 2006-2016. For the first time
completely deserted coal mining technology has been used by the Chinese
concern «China National Coal Group Corp. (CME)» at the mine «Tang Shan
Gou» (longwall mining,
shearers, three lava, depth 200 m), and at the mine «Nan Liang» (one
plow, depth 100 m). Both coal mines have coal layer thickness 1-1.7 m.
Monitoring the harvesting is carried out by means of video cameras (in
real time with signal transmission over optical fiber).
Typically, an underground staff is required to monitor the production
process and for carrying out repairs. Automation has improved the safety
and economic performance.
Next Generation Mining
BHP
have deployed a number of autonomous mining components as part of their
Next Generation Mining program. This includes autonomous drills and autonomous trucks in the Pilbara region.
Autonomy in Europe
In March 2021, Ferrexpo plc announced that it had successfully deployed the first large scale autonomous mining trucks in Europe with the conversion of its CAT 793D haul trucks. The Company has used semi-autonomous drill rigs at its operations since 2017.
An android is a robot or other artificial being designed to resemble a human, and often made from a flesh-like material. Historically, androids were completely within the domain of science fiction and frequently seen in film and television, but recent advances in robot technology now allow the design of functional and realistic humanoid robots.
Etymology
Early example of the term androides used to describe human-like mechanical devices, London Times, 22 December 1795
The word was coined from the Greek root ἀνδρ- andr- "man, male" (as opposed to ἀνθρωπ- anthrōp- "human being") and the suffix -oid "having the form or likeness of".
In Greek, however, ανδροειδής is an adjective. While the term "android"
is used in reference to human-looking robots in general, a robot with a
female appearance can also be referred to as a gynoid.
The Oxford English Dictionary traces the earliest use (as "Androides") to Ephraim Chambers' 1728 Cyclopaedia, in reference to an automaton that St. Albertus Magnus allegedly created.
By the late 1700s "androides", elaborate mechanical devices resembling
humans performing human activities, were displayed in exhibit halls.
The term "android" appears in US patents as early as 1863 in reference to miniature human-like toy automatons. The term android was used in a more modern sense by the French author Auguste Villiers de l'Isle-Adam in his work Tomorrow's Eve (1886).
This story features an artificial humanlike robot named Hadaly. As said
by the officer in the story, "In this age of Realien advancement, who
knows what goes on in the mind of those responsible for these mechanical
dolls." The term made an impact into English pulp science fiction starting from Jack Williamson's The Cometeers (1936) and the distinction between mechanical robots and fleshy androids was popularized by Edmond Hamilton's Captain Future (1940–1944).
Although Karel Čapek's robots in R.U.R. (Rossum's Universal Robots) (1921)—the play that introduced the word robot
to the world—were organic artificial humans, the word "robot" has come
to primarily refer to mechanical humans, animals, and other beings. The term "android" can mean either one of these, while a cyborg ("cybernetic organism" or "bionic man") would be a creature that is a combination of organic and mechanical parts.
Authors have used the term android in more diverse ways than robot or cyborg.
In some fictional works, the difference between a robot and android is
only superficial, with androids being made to look like humans on the
outside but with robot-like internal mechanics. In other stories, authors have used the word "android" to mean a wholly organic, yet artificial, creation. Other fictional depictions of androids fall somewhere in between.
Eric G. Wilson, who defines an android as a "synthetic human
being", distinguishes between three types of android, based on their
body's composition:
the mummy type – made of "dead things" or "stiff, inanimate, natural material", such as mummies, puppets, dolls and statues
the golem type – made from flexible, possibly organic material, including golems and homunculi
the automaton type – made from a mix of dead and living parts, including automatons and robots
Although human morphology is not necessarily the ideal form for
working robots, the fascination in developing robots that can mimic it
can be found historically in the assimilation of two concepts: simulacra (devices that exhibit likeness) and automata (devices that have independence).
Projects
Several
projects aiming to create androids that look, and, to a certain degree,
speak or act like a human being have been launched or are underway.
Japanese robotics have been leading the field since the 1970s. Waseda University
initiated the WABOT project in 1967, and in 1972 completed the WABOT-1,
the first android, a full-scale humanoid intelligent robot. Its limb control system allowed it to walk with the lower limbs, and to grip and transport objects with hands, using tactile sensors.
Its vision system allowed it to measure distances and directions to
objects using external receptors, artificial eyes and ears. And its
conversation system allowed it to communicate with a person in Japanese,
with an artificial mouth.
In 1984, WABOT-2 was revealed, and made a number of improvements.
It was capable of playing the organ. Wabot-2 had ten fingers and two
feet, and was able to read a score of music. It was also able to
accompany a person. In 1986, Honda began its humanoid research and development program, to create humanoid robots capable of interacting successfully with humans.
The Intelligent Robotics Lab, directed by Hiroshi Ishiguro at Osaka University, and the Kokoro company demonstrated the Actroid at Expo 2005 in Aichi Prefecture, Japan and released the Telenoid R1 in 2010. In 2006, Kokoro developed a new DER 2
android. The height of the human body part of DER2 is 165 cm. There are
47 mobile points. DER2 can not only change its expression but also move
its hands and feet and twist its body. The "air servosystem" which
Kokoro developed originally is used for the actuator. As a result of
having an actuator controlled precisely with air pressure via a
servosystem, the movement is very fluid and there is very little noise.
DER2 realized a slimmer body than that of the former version by using a
smaller cylinder. Outwardly DER2 has a more beautiful proportion.
Compared to the previous model, DER2 has thinner arms and a wider
repertoire of expressions. Once programmed, it is able to choreograph
its motions and gestures with its voice.
The Intelligent Mechatronics Lab, directed by Hiroshi Kobayashi at the Tokyo University of Science, has developed an android head called Saya, which was exhibited at Robodex 2002 in Yokohama,
Japan. There are several other initiatives around the world involving
humanoid research and development at this time, which will hopefully
introduce a broader spectrum of realized technology in the near future.
Now Saya is working at the Science University of Tokyo as a guide.
The Waseda University (Japan) and NTT Docomo's manufacturers have succeeded in creating a shape-shifting robot WD-2.
It is capable of changing its face. At first, the creators decided the
positions of the necessary points to express the outline, eyes, nose,
and so on of a certain person. The robot expresses its face by moving
all points to the decided positions, they say. The first version of the
robot was first developed back in 2003. After that, a year later, they
made a couple of major improvements to the design. The robot features an
elastic mask made from the average head dummy. It uses a driving system
with a 3DOF unit. The WD-2 robot can change its facial features by
activating specific facial points on a mask, with each point possessing
three degrees of freedom.
This one has 17 facial points, for a total of 56 degrees of freedom. As
for the materials they used, the WD-2's mask is fabricated with a
highly elastic material called Septom, with bits of steel wool mixed in
for added strength. Other technical features reveal a shaft driven
behind the mask at the desired facial point, driven by a DC motor with a
simple pulley and a slide screw. Apparently, the researchers can also
modify the shape of the mask based on actual human faces. To "copy" a
face, they need only a 3D scanner
to determine the locations of an individual's 17 facial points. After
that, they are then driven into position using a laptop and 56 motor
control boards. In addition, the researchers also mention that the
shifting robot can even display an individual's hair style and skin
color if a photo of their face is projected onto the 3D Mask.
Singapore
Prof
Nadia Thalmann, a Nanyang Technological University scientist, directed
efforts of the Institute for Media Innovation along with the School of
Computer Engineering in the development of a social robot, Nadine.
Nadine is powered by software similar to Apple's Siri or Microsoft's Cortana.
Nadine may become a personal assistant in offices and homes in future,
or she may become a companion for the young and the elderly.
Assoc Prof Gerald Seet from the School of Mechanical &
Aerospace Engineering and the BeingThere Centre led a three-year R&D
development in tele-presence robotics,
creating EDGAR. A remote user can control EDGAR with the user's face
and expressions displayed on the robot's face in real time. The robot
also mimics their upper body movements.
South Korea
EveR-2, the first android that has the ability to sing
KITECH researched and developed EveR-1,
an android interpersonal communications model capable of emulating
human emotional expression via facial "musculature" and capable of
rudimentary conversation, having a vocabulary of around 400 words. She
is 160 cm tall and weighs 50 kg, matching the average figure of a Korean woman in her twenties. EveR-1's name derives from the Biblical Eve, plus the letter r for robot. EveR-1's advanced computing processing power enables speech recognition and vocal synthesis, at the same time processing lip synchronization and visual recognition by 90-degree micro-CCD cameras with face recognition technology.
An independent microchip inside her artificial brain handles gesture
expression, body coordination, and emotion expression. Her whole body is
made of highly advanced synthetic jelly silicon and with 60 artificial
joints in her face, neck, and lower body; she is able to demonstrate
realistic facial expressions and sing while simultaneously dancing. In
South Korea, the Ministry of Information and Communication has an ambitious plan to put a robot in every household by 2020.
Several robot cities have been planned for the country: the first will
be built in 2016 at a cost of 500 billion won (US$440 million), of which
50 billion is direct government investment.
The new robot city will feature research and development centers for
manufacturers and part suppliers, as well as exhibition halls and a
stadium for robot competitions. The country's new Robotics Ethics
Charter will establish ground rules and laws for human interaction with
robots in the future, setting standards for robotics users and
manufacturers, as well as guidelines on ethical standards to be
programmed into robots to prevent human abuse of robots and vice versa.
Dr. William Barry, an Education Futurist and former visiting West Point Professor of Philosophy and Ethical Reasoning at the United States Military Academy,
created an AI android character named "Maria Bot". This Interface AI
android was named after the infamous fictional robot Maria in the 1927
film Metropolis, as a well-behaved distant relative. Maria Bot is the first AI Android Teaching Assistant at the university level. Maria Bot has appeared as a keynote speaker as a duo with Barry for a TEDx talk in Everett, Washington in February 2020.
Dr. William Barry (left) with Maria Bot (right)
Resembling a human from the shoulders up, Maria Bot is a virtual
being android that has complex facial expressions and head movement and
engages in conversation about a variety of subjects. She uses AI to
process and synthesize information to make her own decisions on how to
talk and engage. She collects data through conversations, direct data
inputs such as books or articles, and through internet sources.
Maria Bot was built by an international high-tech company for
Barry to help improve education quality and eliminate education poverty.
Maria Bot is designed to create new ways for students to engage and
discuss ethical issues raised by the increasing presence of robots and
artificial intelligence. Barry also uses Maria Bot to demonstrate that
programming a robot with life-affirming, ethical framework makes them
more likely to help humans to do the same.
Dr. William Barry (right) and a fan pose with Maria Bot (center)
Maria Bot is an ambassador robot for good and ethical AI technology.
Hanson Robotics, Inc., of Texas and KAIST produced an android portrait of Albert Einstein,
using Hanson's facial android technology mounted on KAIST's life-size
walking bipedal robot body. This Einstein android, also called "Albert Hubo", thus represents the first full-body walking android in history. Hanson Robotics, the FedEx Institute of Technology, and the University of Texas at Arlington also developed the android portrait of sci-fi author Philip K. Dick (creator of Do Androids Dream of Electric Sheep?, the basis for the film Blade Runner), with full conversational capabilities that incorporated thousands of pages of the author's works. In 2005, the PKD android won a first-place artificial intelligence award from AAAI.
Use in fiction
Androids are a staple of science fiction. Isaac Asimov pioneered the fictionalization of the science of robotics and artificial intelligence, notably in his 1950s series I, Robot.
One thing common to most fictional androids is that the real-life
technological challenges associated with creating thoroughly human-like
robots—such as the creation of strong artificial intelligence—are assumed to have been solved.
Fictional androids are often depicted as mentally and physically equal
or superior to humans—moving, thinking and speaking as fluidly as them.
The tension between the nonhuman substance and the human
appearance—or even human ambitions—of androids is the dramatic impetus
behind most of their fictional depictions. Some android heroes seek, like Pinocchio, to become human, as in the film Bicentennial Man, or Data in Star Trek: The Next Generation. Others, as in the film Westworld, rebel against abuse by careless humans. Android hunter Deckard in Do Androids Dream of Electric Sheep? and its film adaptation Blade Runner discovers that his targets appear to be, in some ways, more "human" than he is. Android stories, therefore, are not essentially stories "about" androids; they are stories about the human condition and what it means to be human.
One aspect of writing about the meaning of humanity is to use discrimination against androids as a mechanism for exploring racism in society, as in Blade Runner. Perhaps the clearest example of this is John Brunner's 1968 novel Into the Slave Nebula, where the blue-skinned android slaves are explicitly shown to be fully human. More recently, the androids Bishop and Annalee Call in the films Aliens and Alien Resurrection are used as vehicles for exploring how humans deal with the presence of an "Other". The 2018 video game Detroit: Become Human also explores how androids are treated as second class citizens in a near future society.
Female androids, or "gynoids",
are often seen in science fiction, and can be viewed as a continuation
of the long tradition of men attempting to create the stereotypical
"perfect woman". Examples include the Greek myth of Pygmalion and the female robot Maria in Fritz Lang's Metropolis. Some gynoids, like Pris in Blade Runner, are designed as sex-objects, with the intent of "pleasing men's violent sexual desires", or as submissive, servile companions, such as in The Stepford Wives. Fiction about gynoids has therefore been described as reinforcing "essentialist ideas of femininity", although others have suggested that the treatment of androids is a way of exploring racism and misogyny in society.
The 2015 Japanese film Sayonara, starring Geminoid F, was promoted as "the first movie to feature an android performing opposite a human actor".
Articulated industrial robot operating in a foundry.
An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes.
Factory Automation with industrial robots for palletizing food products like bread and toast at a bakery in Germany
There are six types of industrial robots.
Articulated robots
Articulated robots are the most common industrial robots. They look like a human arm, which is why they are also called robotic arm or manipulator arm. Their articulations with several degrees of freedom allow the articulated arms a wide range of movements.
Cartesian coordinate robots
Cartesian robots, also called rectilinear, gantry robots, and x-y-z robots have three prismatic joints for the movement of the tool and three rotary joints for its orientation in space.
To be able to move and orient the effector organ in all
directions, such a robot needs 6 axes (or degrees of freedom). In a
2-dimensional environment, three axes are sufficient, two for
displacement and one for orientation.
Cylindrical coordinate robots
The cylindrical coordinate robots are characterized by their rotary joint at the base and at least one prismatic joint connecting its links.
They can move vertically and horizontally by sliding. The compact
effector design allows the robot to reach tight workspaces without any
loss of speed.
Spherical coordinate robots
Spherical coordinate robots only have rotary joints. They are one of the first robots to have been used in industrial applications. They are commonly used for machine tending in die-casting, plastic injection and extrusion, and for welding.
SCARA robots
SCARA is an acronym for Selective Compliance Assembly Robot Arm. SCARA robots are recognized by their two parallel joints which provide movement in the X-Y plane. Rotating shafts are positioned vertically at the effector..
SCARA robots are used for jobs that require precise lateral movements. They are ideal for assembly applications.
Delta robots
Delta robots are also referred to as parallel link robots.
They consist of parallel links connected to a common base. Delta robots
are particularly useful for direct control tasks and high maneuvering
operations (such as quick pick-and-place tasks). Delta robots take
advantage of four bar or parallelogram linkage systems.
Furthermore, industrial robots can have a serial or parallel architecture.
Serial manipulators
Serial
architectures a.k.a Serial manipulators are the most common industrial
robots and they are designed as a series of links connected by
motor-actuated joints that extend from a base to an end-effector. SCARA ,
Stanford manipulators are typical examples of this category.
Parallel Architecture
A
parallel manipulator is designed so that each chain is usually short,
simple and can thus be rigid against unwanted movement, compared to a serial manipulator.
Errors in one chain's positioning are averaged in conjunction with the
others, rather than being cumulative. Each actuator must still move
within its own degree of freedom,
as for a serial robot; however in the parallel robot the off-axis
flexibility of a joint is also constrained by the effect of the other
chains. It is this closed-loop
stiffness that makes the overall parallel manipulator stiff relative to
its components, unlike the serial chain that becomes progressively less
rigid with more components.
Lower mobility parallel manipulators and concomitant motion
A full parallel manipulator can move an object with up to 6 degrees of freedom (DoF), determined by 3 translation 3T and 3 rotation 3R coordinates for full 3T3R mobility.
However, when a manipulation task requires less than 6 DoF, the use of
lower mobility manipulators, with fewer than 6 DoF, may bring advantages
in terms of simpler architecture, easier control, faster motion and
lower cost. For example, the 3 DoF Delta robot has lower 3T
mobility and has proven to be very successful for rapid pick-and-place
translational positioning applications. The workspace of lower mobility
manipulators may be decomposed into `motion’ and `constraint’ subspaces.
For example, 3 position coordinates constitute the motion subspace of
the 3 DoF Delta robot and the 3 orientation coordinates are in the
constraint subspace. The motion subspace of lower mobility manipulators
may be further decomposed into independent (desired) and dependent
(concomitant) subspaces: consisting of `concomitant’ or `parasitic’
motion which is undesired motion of the manipulator.
The debilitating effects of concomitant motion should be mitigated or
eliminated in the successful design of lower mobility manipulators. For
example, the Delta robot does not have parasitic motion since its end
effector does not rotate.
Autonomy
Robots exhibit varying degrees of autonomy.
Some robots are programmed to faithfully carry out specific actions over
and over again (repetitive actions) without variation and with a high
degree of accuracy. These actions are determined by programmed routines
that specify the direction, acceleration, velocity, deceleration, and
distance of a series of coordinated motions
Other robots are much more flexible as to the orientation of the
object on which they are operating or even the task that has to be
performed on the object itself, which the robot may even need to
identify. For example, for more precise guidance, robots often contain machine vision sub-systems acting as their visual sensors, linked to powerful computers or controllers. Artificial intelligence, or what passes for it, is becoming an increasingly important factor in the modern industrial robot.
History of industrial robotics
The earliest known industrial robot, conforming to the ISO definition was completed by
"Bill" Griffith P. Taylor in 1937 and published in Meccano Magazine, March 1938. The crane-like device was built almost entirely using Meccano parts, and powered by a single electric motor. Five axes of movement were possible, including grab and grab rotation.
Automation was achieved using punched paper tape to energise solenoids,
which would facilitate the movement of the crane's control levers. The robot
could stack wooden blocks in pre-programmed patterns. The number of
motor revolutions required for each desired movement was first plotted
on graph paper. This information was then transferred to the paper tape,
which was also driven by the robot's single motor. Chris Shute built a
complete replica of the robot in 1997.
George Devol, c. 1982
George Devol applied for the first robotics patents in 1954 (granted in 1961). The first company to produce a robot was Unimation, founded by Devol and Joseph F. Engelberger in 1956. Unimation robots were also called programmable transfer machines since their main use at first was to transfer objects from one point to another, less than a dozen feet or so apart. They used hydraulicactuators and were programmed in jointcoordinates,
i.e. the angles of the various joints were stored during a teaching
phase and replayed in operation. They were accurate to within 1/10,000
of an inch
(note: although accuracy is not an appropriate measure for robots,
usually evaluated in terms of repeatability - see later). Unimation
later licensed their technology to Kawasaki Heavy Industries and GKN, manufacturing Unimates in Japan and England respectively. For some time Unimation's only competitor was Cincinnati Milacron Inc. of Ohio. This changed radically in the late 1970s when several big Japanese conglomerates began producing similar industrial robots.
In 1969 Victor Scheinman at Stanford University invented the Stanford arm, an all-electric, 6-axis articulated robot designed to permit an arm solution.
This allowed it accurately to follow arbitrary paths in space and
widened the potential use of the robot to more sophisticated
applications such as assembly and welding. Scheinman then designed a
second arm for the MITAI
Lab, called the "MIT arm." Scheinman, after receiving a fellowship from
Unimation to develop his designs, sold those designs to Unimation who
further developed them with support from General Motors and later marketed it as the Programmable Universal Machine for Assembly (PUMA).
Industrial robotics took off quite quickly in Europe, with both ABB Robotics and KUKA Robotics bringing robots to the market in 1973. ABB Robotics (formerly ASEA) introduced IRB 6, among the world's first commercially available
all electric micro-processor controlled robot. The first two IRB 6
robots were sold to Magnusson in Sweden for grinding and polishing pipe
bends and were installed in production in January 1974. Also in 1973
KUKA Robotics built its first robot, known as FAMULUS, also one of the first articulated robots to have six electromechanically driven axes.
Number of axes
– two axes are required to reach any point in a plane; three axes are
required to reach any point in space. To fully control the orientation
of the end of the arm(i.e. the wrist) three more axes (yaw, pitch, and roll) are required. Some designs (e.g. the SCARA robot) trade limitations in motion possibilities for cost, speed, and accuracy.
Kinematics – the actual arrangement of rigid members and joints in the robot, which determines the robot's possible motions. Classes of robot kinematics include articulated, cartesian, parallel and SCARA.
Carrying capacity or payload – how much weight a robot can lift.
Speed – how fast the robot can position the end of its arm.
This may be defined in terms of the angular or linear speed of each axis
or as a compound speed i.e. the speed of the end of the arm when all
axes are moving.
Acceleration – how quickly an axis can accelerate. Since this
is a limiting factor a robot may not be able to reach its specified
maximum speed for movements over a short distance or a complex path
requiring frequent changes of direction.
Accuracy – how closely a robot can reach a commanded
position. When the absolute position of the robot is measured and
compared to the commanded position the error is a measure of accuracy.
Accuracy can be improved with external sensing for example a vision
system or Infra-Red. See robot calibration. Accuracy can vary with speed and position within the working envelope and with payload (see compliance).
Repeatability – how well the robot will return to a
programmed position. This is not the same as accuracy. It may be that
when told to go to a certain X-Y-Z position that it gets only to within
1 mm of that position. This would be its accuracy which may be improved
by calibration. But if that position is taught into controller memory
and each time it is sent there it returns to within 0.1mm of the taught
position then the repeatability will be within 0.1mm.
Accuracy and repeatability are different measures. Repeatability is
usually the most important criterion for a robot and is similar to the
concept of 'precision' in measurement—see accuracy and precision. ISO 9283
sets out a method whereby both accuracy and repeatability can be
measured. Typically a robot is sent to a taught position a number of
times and the error is measured at each return to the position after
visiting 4 other positions. Repeatability is then quantified using the standard deviation
of those samples in all three dimensions. A typical robot can, of
course make a positional error exceeding that and that could be a
problem for the process. Moreover, the repeatability is different in
different parts of the working envelope and also changes with speed and
payload. ISO 9283 specifies that accuracy and repeatability should be
measured at maximum speed and at maximum payload. But this results in
pessimistic values whereas the robot could be much more accurate and
repeatable at light loads and speeds.
Repeatability in an industrial process is also subject to the accuracy
of the end effector, for example a gripper, and even to the design of
the 'fingers' that match the gripper to the object being grasped. For
example, if a robot picks a screw by its head, the screw could be at a
random angle. A subsequent attempt to insert the screw into a hole could
easily fail. These and similar scenarios can be improved with
'lead-ins' e.g. by making the entrance to the hole tapered.
Motion control – for some applications, such as simple
pick-and-place assembly, the robot need merely return repeatably to a
limited number of pre-taught positions. For more sophisticated
applications, such as welding and finishing (spray painting), motion must be continuously controlled to follow a path in space, with controlled orientation and velocity.
Power source – some robots use electric motors, others use hydraulic
actuators. The former are faster, the latter are stronger and
advantageous in applications such as spray painting, where a spark could
set off an explosion;
however, low internal air-pressurisation of the arm can prevent ingress
of flammable vapours as well as other contaminants. Nowadays, it is
highly unlikely to see any hydraulic robots in the market. Additional
sealings, brushless electric motors and spark-proof protection eased the
construction of units that are able to work in the environment with an
explosive atmosphere.
Drive – some robots connect electric motors to the joints via gears; others connect the motor to the joint directly (direct drive).
Using gears results in measurable 'backlash' which is free movement in
an axis. Smaller robot arms frequently employ high speed, low torque DC
motors, which generally require high gearing ratios; this has the
disadvantage of backlash. In such cases the harmonic drive is often used.
Compliance - this is a measure of the amount in angle or
distance that a robot axis will move when a force is applied to it.
Because of compliance when a robot goes to a position carrying its
maximum payload it will be at a position slightly lower than when it is
carrying no payload. Compliance can also be responsible for overshoot
when carrying high payloads in which case acceleration would need to be
reduced.
Robot programming and interfaces
Offline programming
A typical well-used teach pendant with optional mouse
The setup or programming of motions and sequences for an industrial robot is typically taught by linking the robot controller to a laptop, desktop computer or (internal or Internet) network.
A robot and a collection of machines or peripherals is referred to as a workcell, or cell. A typical cell might contain a parts feeder, a molding machine and a robot. The various machines are 'integrated' and controlled by a single computer or PLC.
How the robot interacts with other machines in the cell must be
programmed, both with regard to their positions in the cell and
synchronizing with them.
Software: The computer is installed with corresponding interface software. The use of a computer greatly simplifies the programming process. Specialized robot software is run either in the robot controller or in the computer or both depending on the system design.
There are two basic entities that need to be taught (or
programmed): positional data and procedure. For example, in a task to
move a screw from a feeder to a hole the positions of the feeder and the
hole must first be taught or programmed. Secondly the procedure to get
the screw from the feeder to the hole must be programmed along with any
I/O involved, for example a signal to indicate when the screw is in the
feeder ready to be picked up. The purpose of the robot software is to
facilitate both these programming tasks.
Teaching the robot positions may be achieved a number of ways:
Positional commands The robot can be directed to the required position using a GUI or text based commands in which the required X-Y-Z position may be specified and edited.
Teach pendant: Robot positions can be taught via a teach pendant.
This is a handheld control and programming unit. The common features of
such units are the ability to manually send the robot to a desired
position, or "inch" or "jog" to adjust a position. They also have a
means to change the speed since a low speed is usually required for
careful positioning, or while test-running through a new or modified
routine. A large emergency stop
button is usually included as well. Typically once the robot has been
programmed there is no more use for the teach pendant. All teach
pendants are equipped with a 3-position deadman switch.
In the manual mode, it allows the robot to move only when it is in the
middle position (partially pressed). If it is fully pressed in or
completely released, the robot stops. This principle of operation allows
natural reflexes to be used to increase safety.
Lead-by-the-nose: this is a technique offered by many
robot manufacturers. In this method, one user holds the robot's
manipulator, while another person enters a command which de-energizes
the robot causing it to go into limp. The user then moves the robot by
hand to the required positions and/or along a required path while the
software logs these positions into memory. The program can later run the
robot to these positions or along the taught path. This technique is
popular for tasks such as paint spraying.
Offline programming is where the entire cell, the robot and
all the machines or instruments in the workspace are mapped graphically.
The robot can then be moved on screen and the process simulated. A
robotics simulator is used to create embedded applications for a robot,
without depending on the physical operation of the robot arm and end
effector. The advantages of robotics simulation is that it saves time in
the design of robotics applications. It can also increase the level of
safety associated with robotic equipment since various "what if"
scenarios can be tried and tested before the system is activated.[8]
Robot simulation software provides a platform to teach, test, run, and
debug programs that have been written in a variety of programming
languages.
Robotics Simulator
Robot simulation tools allow for robotics programs to be
conveniently written and debugged off-line with the final version of the
program tested on an actual robot. The ability to preview the behavior
of a robotic system in a virtual world allows for a variety of
mechanisms, devices, configurations and controllers to be tried and
tested before being applied to a "real world" system. Robotics
simulators have the ability to provide real-time computing of the
simulated motion of an industrial robot using both geometric modeling
and kinematics modeling.
Manufacturing independent robot programming tools are a relatively new but flexible way to program robot applications. Using a graphical user interface
the programming is done via drag and drop of predefined
template/building blocks. They often feature the execution of
simulations to evaluate the feasibility and offline programming
in combination. If the system is able to compile and upload native
robot code to the robot controller, the user no longer has to learn each
manufacturer's proprietary language. Therefore, this approach can be an important step to standardize programming methods.
Others in addition, machine operators often use user interface devices, typically touchscreen
units, which serve as the operator control panel. The operator can
switch from program to program, make adjustments within a program and
also operate a host of peripheral devices that may be integrated within the same robotic system. These include end effectors, feeders that supply components to the robot, conveyor belts, emergency stop controls, machine vision systems, safety interlock systems, barcode
printers and an almost infinite array of other industrial devices which
are accessed and controlled via the operator control panel.
The teach pendant or PC is usually disconnected after programming
and the robot then runs on the program that has been installed in its controller.
However a computer is often used to 'supervise' the robot and any
peripherals, or to provide additional storage for access to numerous
complex paths and routines.
End-of-arm tooling
The most essential robot peripheral is the end effector,
or end-of-arm-tooling (EOT). Common examples of end effectors include
welding devices (such as MIG-welding guns, spot-welders, etc.), spray
guns and also grinding and deburring devices (such as pneumatic disk or
belt grinders, burrs, etc.), and grippers (devices that can grasp an
object, usually electromechanical or pneumatic). Other common means of picking up objects is by vacuum or magnets.
End effectors are frequently highly complex, made to match the handled
product and often capable of picking up an array of products at one
time. They may utilize various sensors to aid the robot system in
locating, handling, and positioning products.
Controlling movement
For
a given robot the only parameters necessary to completely locate the
end effector (gripper, welding torch, etc.) of the robot are the angles
of each of the joints or displacements of the linear axes (or
combinations of the two for robot formats such as SCARA). However, there
are many different ways to define the points. The most common and most
convenient way of defining a point is to specify a Cartesian coordinate
for it, i.e. the position of the 'end effector' in mm in the X, Y and Z
directions relative to the robot's origin. In addition, depending on
the types of joints a particular robot may have, the orientation of the
end effector in yaw, pitch, and roll and the location of the tool point
relative to the robot's faceplate must also be specified. For a jointed arm
these coordinates must be converted to joint angles by the robot
controller and such conversions are known as Cartesian Transformations
which may need to be performed iteratively or recursively for a multiple
axis robot. The mathematics of the relationship between joint angles
and actual spatial coordinates is called kinematics.
Positioning by Cartesian coordinates may be done by entering the
coordinates into the system or by using a teach pendant which moves the
robot in X-Y-Z directions. It is much easier for a human operator to
visualize motions up/down, left/right, etc. than to move each joint one
at a time. When the desired position is reached it is then defined in
some way particular to the robot software in use, e.g. P1 - P5 below.
Typical programming
Most
articulated robots perform by storing a series of positions in memory,
and moving to them at various times in their programming sequence. For
example, a robot which is moving items from one place (bin A) to another
(bin B) might have a simple 'pick and place' program similar to the
following:
Define points P1–P5:
Safely above workpiece (defined as P1)
10 cm Above bin A (defined as P2)
At position to take part from bin A (defined as P3)
10 cm Above bin B (defined as P4)
At position to take part from bin B. (defined as P5)
The
American National Standard for Industrial Robots and Robot Systems —
Safety Requirements (ANSI/RIA R15.06-1999) defines a singularity as “a
condition caused by the collinear alignment of two or more robot axes
resulting in unpredictable robot motion and velocities.” It is most
common in robot arms that utilize a “triple-roll wrist”. This is a wrist
about which the three axes of the wrist, controlling yaw, pitch, and
roll, all pass through a common point. An example of a wrist singularity
is when the path through which the robot is traveling causes the first
and third axes of the robot's wrist (i.e. robot's axes 4 and 6) to line
up. The second wrist axis then attempts to spin 180° in zero time to
maintain the orientation of the end effector. Another common term for
this singularity is a “wrist flip”. The result of a singularity can be
quite dramatic and can have adverse effects on the robot arm, the end
effector, and the process. Some industrial robot manufacturers have
attempted to side-step the situation by slightly altering the robot's
path to prevent this condition. Another method is to slow the robot's
travel speed, thus reducing the speed required for the wrist to make the
transition. The ANSI/RIA has mandated that robot manufacturers shall
make the user aware of singularities if they occur while the system is
being manually manipulated.
A second type of singularity in wrist-partitioned vertically
articulated six-axis robots occurs when the wrist center lies on a
cylinder that is centered about axis 1 and with radius equal to the
distance between axes 1 and 4. This is called a shoulder singularity.
Some robot manufacturers also mention alignment singularities, where
axes 1 and 6 become coincident. This is simply a sub-case of shoulder
singularities. When the robot passes close to a shoulder singularity,
joint 1 spins very fast.
The third and last type of singularity in wrist-partitioned
vertically articulated six-axis robots occurs when the wrist's center
lies in the same plane as axes 2 and 3.
Singularities are closely related to the phenomena of gimbal lock, which has a similar root cause of axes becoming lined up.
Market structure
According to the International Federation of Robotics (IFR) study World Robotics 2019,
there were about 2,439,543 operational industrial robots by the end of
2017. This number is estimated to reach 3,788,000 by the end of 2021.
For the year 2018 the IFR estimates the worldwide sales of industrial
robots with US$16.5 billion. Including the cost of software, peripherals
and systems engineering, the annual turnover for robot systems is
estimated to be US$48.0 billion in 2018.
China is the largest industrial robot market, with 154,032 units sold in 2018. China had the largest operational stock of industrial robots, with 649,447 at the end of 2018.
The United States industrial robot-makers shipped 35,880 robot to
factories in the US in 2018 and this was 7% more than in 2017.
The biggest customer of industrial robots is automotive industry
with 30% market share, then electrical/electronics industry with 25%,
metal and machinery industry with 10%, rubber and plastics industry with
5%, food industry with 5%. In textiles, apparel and leather industry, 1,580 units are operational.
Estimated worldwide annual supply of industrial robots (in units):
The International Federation of Robotics
has predicted a worldwide increase in adoption of industrial robots and
they estimated 1.7 million new robot installations in factories
worldwide by 2020 [IFR 2017].
Rapid advances in automation technologies (e.g. fixed robots,
collaborative and mobile robots, and exoskeletons) have the potential to
improve work conditions but also to introduce workplace hazards in
manufacturing workplaces. Despite the lack of occupational surveillance data on injuries associated specifically with robots, researchers from the US National Institute for Occupational Safety and Health (NIOSH) identified 61 robot-related deaths between 1992 and 2015 using keyword searches of the Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries research database (see info from Center for Occupational Robotics Research).
Using data from the Bureau of Labor Statistics, NIOSH and its state
partners have investigated 4 robot-related fatalities under the Fatality Assessment and Control Evaluation Program.
In addition the Occupational Safety and Health Administration (OSHA)
has investigated dozens of robot-related deaths and injuries, which can
be reviewed at OSHA Accident Search page.
Injuries and fatalities could increase over time because of the
increasing number of collaborative and co-existing robots, powered
exoskeletons, and autonomous vehicles into the work environment.
Safety standards are being developed by the Robotic Industries Association (RIA) in conjunction with the American National Standards Institute (ANSI). On October 5, 2017, OSHA, NIOSH and RIA signed an alliance
to work together to enhance technical expertise, identify and help
address potential workplace hazards associated with traditional
industrial robots and the emerging technology of human-robot
collaboration installations and systems, and help identify needed
research to reduce workplace hazards. On October 16 NIOSH launched the Center for Occupational Robotics Research
to "provide scientific leadership to guide the development and use of
occupational robots that enhance worker safety, health, and wellbeing."
So far, the research needs identified by NIOSH and its partners
include: tracking and preventing injuries and fatalities, intervention
and dissemination strategies to promote safe machine control and
maintenance procedures, and on translating effective evidence-based
interventions into workplace practice.
Articulated industrial robot operating in a foundry.
An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes.
Factory Automation with industrial robots for palletizing food products like bread and toast at a bakery in Germany
There are six types of industrial robots.
Articulated robots
Articulated robots are the most common industrial robots. They look like a human arm, which is why they are also called robotic arm or manipulator arm. Their articulations with several degrees of freedom allow the articulated arms a wide range of movements.
Cartesian coordinate robots
Cartesian robots, also called rectilinear, gantry robots, and x-y-z robots have three prismatic joints for the movement of the tool and three rotary joints for its orientation in space.
To be able to move and orient the effector organ in all
directions, such a robot needs 6 axes (or degrees of freedom). In a
2-dimensional environment, three axes are sufficient, two for
displacement and one for orientation.
Cylindrical coordinate robots
The cylindrical coordinate robots are characterized by their rotary joint at the base and at least one prismatic joint connecting its links.
They can move vertically and horizontally by sliding. The compact
effector design allows the robot to reach tight workspaces without any
loss of speed.
Spherical coordinate robots
Spherical coordinate robots only have rotary joints. They are one of the first robots to have been used in industrial applications. They are commonly used for machine tending in die-casting, plastic injection and extrusion, and for welding.
SCARA robots
SCARA is an acronym for Selective Compliance Assembly Robot Arm. SCARA robots are recognized by their two parallel joints which provide movement in the X-Y plane. Rotating shafts are positioned vertically at the effector..
SCARA robots are used for jobs that require precise lateral movements. They are ideal for assembly applications.
Delta robots
Delta robots are also referred to as parallel link robots.
They consist of parallel links connected to a common base. Delta robots
are particularly useful for direct control tasks and high maneuvering
operations (such as quick pick-and-place tasks). Delta robots take
advantage of four bar or parallelogram linkage systems.
Furthermore, industrial robots can have a serial or parallel architecture.
Serial manipulators
Serial
architectures a.k.a Serial manipulators are the most common industrial
robots and they are designed as a series of links connected by
motor-actuated joints that extend from a base to an end-effector. SCARA ,
Stanford manipulators are typical examples of this category.
Parallel Architecture
A
parallel manipulator is designed so that each chain is usually short,
simple and can thus be rigid against unwanted movement, compared to a serial manipulator.
Errors in one chain's positioning are averaged in conjunction with the
others, rather than being cumulative. Each actuator must still move
within its own degree of freedom,
as for a serial robot; however in the parallel robot the off-axis
flexibility of a joint is also constrained by the effect of the other
chains. It is this closed-loop
stiffness that makes the overall parallel manipulator stiff relative to
its components, unlike the serial chain that becomes progressively less
rigid with more components.
Lower mobility parallel manipulators and concomitant motion
A full parallel manipulator can move an object with up to 6 degrees of freedom (DoF), determined by 3 translation 3T and 3 rotation 3R coordinates for full 3T3R mobility.
However, when a manipulation task requires less than 6 DoF, the use of
lower mobility manipulators, with fewer than 6 DoF, may bring advantages
in terms of simpler architecture, easier control, faster motion and
lower cost. For example, the 3 DoF Delta robot has lower 3T
mobility and has proven to be very successful for rapid pick-and-place
translational positioning applications. The workspace of lower mobility
manipulators may be decomposed into `motion’ and `constraint’ subspaces.
For example, 3 position coordinates constitute the motion subspace of
the 3 DoF Delta robot and the 3 orientation coordinates are in the
constraint subspace. The motion subspace of lower mobility manipulators
may be further decomposed into independent (desired) and dependent
(concomitant) subspaces: consisting of `concomitant’ or `parasitic’
motion which is undesired motion of the manipulator.
The debilitating effects of concomitant motion should be mitigated or
eliminated in the successful design of lower mobility manipulators. For
example, the Delta robot does not have parasitic motion since its end
effector does not rotate.
Autonomy
Robots exhibit varying degrees of autonomy.
Some robots are programmed to faithfully carry out specific actions over
and over again (repetitive actions) without variation and with a high
degree of accuracy. These actions are determined by programmed routines
that specify the direction, acceleration, velocity, deceleration, and
distance of a series of coordinated motions
Other robots are much more flexible as to the orientation of the
object on which they are operating or even the task that has to be
performed on the object itself, which the robot may even need to
identify. For example, for more precise guidance, robots often contain machine vision sub-systems acting as their visual sensors, linked to powerful computers or controllers. Artificial intelligence, or what passes for it, is becoming an increasingly important factor in the modern industrial robot.
History of industrial robotics
The earliest known industrial robot, conforming to the ISO definition was completed by
"Bill" Griffith P. Taylor in 1937 and published in Meccano Magazine, March 1938. The crane-like device was built almost entirely using Meccano parts, and powered by a single electric motor. Five axes of movement were possible, including grab and grab rotation.
Automation was achieved using punched paper tape to energise solenoids,
which would facilitate the movement of the crane's control levers. The robot
could stack wooden blocks in pre-programmed patterns. The number of
motor revolutions required for each desired movement was first plotted
on graph paper. This information was then transferred to the paper tape,
which was also driven by the robot's single motor. Chris Shute built a
complete replica of the robot in 1997.
George Devol, c. 1982
George Devol applied for the first robotics patents in 1954 (granted in 1961). The first company to produce a robot was Unimation, founded by Devol and Joseph F. Engelberger in 1956. Unimation robots were also called programmable transfer machines since their main use at first was to transfer objects from one point to another, less than a dozen feet or so apart. They used hydraulicactuators and were programmed in jointcoordinates,
i.e. the angles of the various joints were stored during a teaching
phase and replayed in operation. They were accurate to within 1/10,000
of an inch
(note: although accuracy is not an appropriate measure for robots,
usually evaluated in terms of repeatability - see later). Unimation
later licensed their technology to Kawasaki Heavy Industries and GKN, manufacturing Unimates in Japan and England respectively. For some time Unimation's only competitor was Cincinnati Milacron Inc. of Ohio. This changed radically in the late 1970s when several big Japanese conglomerates began producing similar industrial robots.
In 1969 Victor Scheinman at Stanford University invented the Stanford arm, an all-electric, 6-axis articulated robot designed to permit an arm solution.
This allowed it accurately to follow arbitrary paths in space and
widened the potential use of the robot to more sophisticated
applications such as assembly and welding. Scheinman then designed a
second arm for the MITAI
Lab, called the "MIT arm." Scheinman, after receiving a fellowship from
Unimation to develop his designs, sold those designs to Unimation who
further developed them with support from General Motors and later marketed it as the Programmable Universal Machine for Assembly (PUMA).
Industrial robotics took off quite quickly in Europe, with both ABB Robotics and KUKA Robotics bringing robots to the market in 1973. ABB Robotics (formerly ASEA) introduced IRB 6, among the world's first commercially available
all electric micro-processor controlled robot. The first two IRB 6
robots were sold to Magnusson in Sweden for grinding and polishing pipe
bends and were installed in production in January 1974. Also in 1973
KUKA Robotics built its first robot, known as FAMULUS, also one of the first articulated robots to have six electromechanically driven axes.
Number of axes
– two axes are required to reach any point in a plane; three axes are
required to reach any point in space. To fully control the orientation
of the end of the arm(i.e. the wrist) three more axes (yaw, pitch, and roll) are required. Some designs (e.g. the SCARA robot) trade limitations in motion possibilities for cost, speed, and accuracy.
Kinematics – the actual arrangement of rigid members and joints in the robot, which determines the robot's possible motions. Classes of robot kinematics include articulated, cartesian, parallel and SCARA.
Carrying capacity or payload – how much weight a robot can lift.
Speed – how fast the robot can position the end of its arm.
This may be defined in terms of the angular or linear speed of each axis
or as a compound speed i.e. the speed of the end of the arm when all
axes are moving.
Acceleration – how quickly an axis can accelerate. Since this
is a limiting factor a robot may not be able to reach its specified
maximum speed for movements over a short distance or a complex path
requiring frequent changes of direction.
Accuracy – how closely a robot can reach a commanded
position. When the absolute position of the robot is measured and
compared to the commanded position the error is a measure of accuracy.
Accuracy can be improved with external sensing for example a vision
system or Infra-Red. See robot calibration. Accuracy can vary with speed and position within the working envelope and with payload (see compliance).
Repeatability – how well the robot will return to a
programmed position. This is not the same as accuracy. It may be that
when told to go to a certain X-Y-Z position that it gets only to within
1 mm of that position. This would be its accuracy which may be improved
by calibration. But if that position is taught into controller memory
and each time it is sent there it returns to within 0.1mm of the taught
position then the repeatability will be within 0.1mm.
Accuracy and repeatability are different measures. Repeatability is
usually the most important criterion for a robot and is similar to the
concept of 'precision' in measurement—see accuracy and precision. ISO 9283
sets out a method whereby both accuracy and repeatability can be
measured. Typically a robot is sent to a taught position a number of
times and the error is measured at each return to the position after
visiting 4 other positions. Repeatability is then quantified using the standard deviation
of those samples in all three dimensions. A typical robot can, of
course make a positional error exceeding that and that could be a
problem for the process. Moreover, the repeatability is different in
different parts of the working envelope and also changes with speed and
payload. ISO 9283 specifies that accuracy and repeatability should be
measured at maximum speed and at maximum payload. But this results in
pessimistic values whereas the robot could be much more accurate and
repeatable at light loads and speeds.
Repeatability in an industrial process is also subject to the accuracy
of the end effector, for example a gripper, and even to the design of
the 'fingers' that match the gripper to the object being grasped. For
example, if a robot picks a screw by its head, the screw could be at a
random angle. A subsequent attempt to insert the screw into a hole could
easily fail. These and similar scenarios can be improved with
'lead-ins' e.g. by making the entrance to the hole tapered.
Motion control – for some applications, such as simple
pick-and-place assembly, the robot need merely return repeatably to a
limited number of pre-taught positions. For more sophisticated
applications, such as welding and finishing (spray painting), motion must be continuously controlled to follow a path in space, with controlled orientation and velocity.
Power source – some robots use electric motors, others use hydraulic
actuators. The former are faster, the latter are stronger and
advantageous in applications such as spray painting, where a spark could
set off an explosion;
however, low internal air-pressurisation of the arm can prevent ingress
of flammable vapours as well as other contaminants. Nowadays, it is
highly unlikely to see any hydraulic robots in the market. Additional
sealings, brushless electric motors and spark-proof protection eased the
construction of units that are able to work in the environment with an
explosive atmosphere.
Drive – some robots connect electric motors to the joints via gears; others connect the motor to the joint directly (direct drive).
Using gears results in measurable 'backlash' which is free movement in
an axis. Smaller robot arms frequently employ high speed, low torque DC
motors, which generally require high gearing ratios; this has the
disadvantage of backlash. In such cases the harmonic drive is often used.
Compliance - this is a measure of the amount in angle or
distance that a robot axis will move when a force is applied to it.
Because of compliance when a robot goes to a position carrying its
maximum payload it will be at a position slightly lower than when it is
carrying no payload. Compliance can also be responsible for overshoot
when carrying high payloads in which case acceleration would need to be
reduced.
Robot programming and interfaces
Offline programming
A typical well-used teach pendant with optional mouse
The setup or programming of motions and sequences for an industrial robot is typically taught by linking the robot controller to a laptop, desktop computer or (internal or Internet) network.
A robot and a collection of machines or peripherals is referred to as a workcell, or cell. A typical cell might contain a parts feeder, a molding machine and a robot. The various machines are 'integrated' and controlled by a single computer or PLC.
How the robot interacts with other machines in the cell must be
programmed, both with regard to their positions in the cell and
synchronizing with them.
Software: The computer is installed with corresponding interface software. The use of a computer greatly simplifies the programming process. Specialized robot software is run either in the robot controller or in the computer or both depending on the system design.
There are two basic entities that need to be taught (or
programmed): positional data and procedure. For example, in a task to
move a screw from a feeder to a hole the positions of the feeder and the
hole must first be taught or programmed. Secondly the procedure to get
the screw from the feeder to the hole must be programmed along with any
I/O involved, for example a signal to indicate when the screw is in the
feeder ready to be picked up. The purpose of the robot software is to
facilitate both these programming tasks.
Teaching the robot positions may be achieved a number of ways:
Positional commands The robot can be directed to the required position using a GUI or text based commands in which the required X-Y-Z position may be specified and edited.
Teach pendant: Robot positions can be taught via a teach pendant.
This is a handheld control and programming unit. The common features of
such units are the ability to manually send the robot to a desired
position, or "inch" or "jog" to adjust a position. They also have a
means to change the speed since a low speed is usually required for
careful positioning, or while test-running through a new or modified
routine. A large emergency stop
button is usually included as well. Typically once the robot has been
programmed there is no more use for the teach pendant. All teach
pendants are equipped with a 3-position deadman switch.
In the manual mode, it allows the robot to move only when it is in the
middle position (partially pressed). If it is fully pressed in or
completely released, the robot stops. This principle of operation allows
natural reflexes to be used to increase safety.
Lead-by-the-nose: this is a technique offered by many
robot manufacturers. In this method, one user holds the robot's
manipulator, while another person enters a command which de-energizes
the robot causing it to go into limp. The user then moves the robot by
hand to the required positions and/or along a required path while the
software logs these positions into memory. The program can later run the
robot to these positions or along the taught path. This technique is
popular for tasks such as paint spraying.
Offline programming is where the entire cell, the robot and
all the machines or instruments in the workspace are mapped graphically.
The robot can then be moved on screen and the process simulated. A
robotics simulator is used to create embedded applications for a robot,
without depending on the physical operation of the robot arm and end
effector. The advantages of robotics simulation is that it saves time in
the design of robotics applications. It can also increase the level of
safety associated with robotic equipment since various "what if"
scenarios can be tried and tested before the system is activated.[8]
Robot simulation software provides a platform to teach, test, run, and
debug programs that have been written in a variety of programming
languages.
Robotics Simulator
Robot simulation tools allow for robotics programs to be
conveniently written and debugged off-line with the final version of the
program tested on an actual robot. The ability to preview the behavior
of a robotic system in a virtual world allows for a variety of
mechanisms, devices, configurations and controllers to be tried and
tested before being applied to a "real world" system. Robotics
simulators have the ability to provide real-time computing of the
simulated motion of an industrial robot using both geometric modeling
and kinematics modeling.
Manufacturing independent robot programming tools are a relatively new but flexible way to program robot applications. Using a graphical user interface
the programming is done via drag and drop of predefined
template/building blocks. They often feature the execution of
simulations to evaluate the feasibility and offline programming
in combination. If the system is able to compile and upload native
robot code to the robot controller, the user no longer has to learn each
manufacturer's proprietary language. Therefore, this approach can be an important step to standardize programming methods.
Others in addition, machine operators often use user interface devices, typically touchscreen
units, which serve as the operator control panel. The operator can
switch from program to program, make adjustments within a program and
also operate a host of peripheral devices that may be integrated within the same robotic system. These include end effectors, feeders that supply components to the robot, conveyor belts, emergency stop controls, machine vision systems, safety interlock systems, barcode
printers and an almost infinite array of other industrial devices which
are accessed and controlled via the operator control panel.
The teach pendant or PC is usually disconnected after programming
and the robot then runs on the program that has been installed in its controller.
However a computer is often used to 'supervise' the robot and any
peripherals, or to provide additional storage for access to numerous
complex paths and routines.
End-of-arm tooling
The most essential robot peripheral is the end effector,
or end-of-arm-tooling (EOT). Common examples of end effectors include
welding devices (such as MIG-welding guns, spot-welders, etc.), spray
guns and also grinding and deburring devices (such as pneumatic disk or
belt grinders, burrs, etc.), and grippers (devices that can grasp an
object, usually electromechanical or pneumatic). Other common means of picking up objects is by vacuum or magnets.
End effectors are frequently highly complex, made to match the handled
product and often capable of picking up an array of products at one
time. They may utilize various sensors to aid the robot system in
locating, handling, and positioning products.
Controlling movement
For
a given robot the only parameters necessary to completely locate the
end effector (gripper, welding torch, etc.) of the robot are the angles
of each of the joints or displacements of the linear axes (or
combinations of the two for robot formats such as SCARA). However, there
are many different ways to define the points. The most common and most
convenient way of defining a point is to specify a Cartesian coordinate
for it, i.e. the position of the 'end effector' in mm in the X, Y and Z
directions relative to the robot's origin. In addition, depending on
the types of joints a particular robot may have, the orientation of the
end effector in yaw, pitch, and roll and the location of the tool point
relative to the robot's faceplate must also be specified. For a jointed arm
these coordinates must be converted to joint angles by the robot
controller and such conversions are known as Cartesian Transformations
which may need to be performed iteratively or recursively for a multiple
axis robot. The mathematics of the relationship between joint angles
and actual spatial coordinates is called kinematics.
Positioning by Cartesian coordinates may be done by entering the
coordinates into the system or by using a teach pendant which moves the
robot in X-Y-Z directions. It is much easier for a human operator to
visualize motions up/down, left/right, etc. than to move each joint one
at a time. When the desired position is reached it is then defined in
some way particular to the robot software in use, e.g. P1 - P5 below.
Typical programming
Most
articulated robots perform by storing a series of positions in memory,
and moving to them at various times in their programming sequence. For
example, a robot which is moving items from one place (bin A) to another
(bin B) might have a simple 'pick and place' program similar to the
following:
Define points P1–P5:
Safely above workpiece (defined as P1)
10 cm Above bin A (defined as P2)
At position to take part from bin A (defined as P3)
10 cm Above bin B (defined as P4)
At position to take part from bin B. (defined as P5)
The
American National Standard for Industrial Robots and Robot Systems —
Safety Requirements (ANSI/RIA R15.06-1999) defines a singularity as “a
condition caused by the collinear alignment of two or more robot axes
resulting in unpredictable robot motion and velocities.” It is most
common in robot arms that utilize a “triple-roll wrist”. This is a wrist
about which the three axes of the wrist, controlling yaw, pitch, and
roll, all pass through a common point. An example of a wrist singularity
is when the path through which the robot is traveling causes the first
and third axes of the robot's wrist (i.e. robot's axes 4 and 6) to line
up. The second wrist axis then attempts to spin 180° in zero time to
maintain the orientation of the end effector. Another common term for
this singularity is a “wrist flip”. The result of a singularity can be
quite dramatic and can have adverse effects on the robot arm, the end
effector, and the process. Some industrial robot manufacturers have
attempted to side-step the situation by slightly altering the robot's
path to prevent this condition. Another method is to slow the robot's
travel speed, thus reducing the speed required for the wrist to make the
transition. The ANSI/RIA has mandated that robot manufacturers shall
make the user aware of singularities if they occur while the system is
being manually manipulated.
A second type of singularity in wrist-partitioned vertically
articulated six-axis robots occurs when the wrist center lies on a
cylinder that is centered about axis 1 and with radius equal to the
distance between axes 1 and 4. This is called a shoulder singularity.
Some robot manufacturers also mention alignment singularities, where
axes 1 and 6 become coincident. This is simply a sub-case of shoulder
singularities. When the robot passes close to a shoulder singularity,
joint 1 spins very fast.
The third and last type of singularity in wrist-partitioned
vertically articulated six-axis robots occurs when the wrist's center
lies in the same plane as axes 2 and 3.
Singularities are closely related to the phenomena of gimbal lock, which has a similar root cause of axes becoming lined up.
Market structure
According to the International Federation of Robotics (IFR) study World Robotics 2019,
there were about 2,439,543 operational industrial robots by the end of
2017. This number is estimated to reach 3,788,000 by the end of 2021.
For the year 2018 the IFR estimates the worldwide sales of industrial
robots with US$16.5 billion. Including the cost of software, peripherals
and systems engineering, the annual turnover for robot systems is
estimated to be US$48.0 billion in 2018.
China is the largest industrial robot market, with 154,032 units sold in 2018. China had the largest operational stock of industrial robots, with 649,447 at the end of 2018.
The United States industrial robot-makers shipped 35,880 robot to
factories in the US in 2018 and this was 7% more than in 2017.
The biggest customer of industrial robots is automotive industry
with 30% market share, then electrical/electronics industry with 25%,
metal and machinery industry with 10%, rubber and plastics industry with
5%, food industry with 5%. In textiles, apparel and leather industry, 1,580 units are operational.
Estimated worldwide annual supply of industrial robots (in units):
The International Federation of Robotics
has predicted a worldwide increase in adoption of industrial robots and
they estimated 1.7 million new robot installations in factories
worldwide by 2020.
Rapid advances in automation technologies (e.g. fixed robots,
collaborative and mobile robots, and exoskeletons) have the potential to
improve work conditions but also to introduce workplace hazards in
manufacturing workplaces. Despite the lack of occupational surveillance data on injuries associated specifically with robots, researchers from the US National Institute for Occupational Safety and Health (NIOSH) identified 61 robot-related deaths between 1992 and 2015 using keyword searches of the Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries research database (see info from Center for Occupational Robotics Research).
Using data from the Bureau of Labor Statistics, NIOSH and its state
partners have investigated 4 robot-related fatalities under the Fatality Assessment and Control Evaluation Program.
In addition the Occupational Safety and Health Administration (OSHA)
has investigated dozens of robot-related deaths and injuries, which can
be reviewed at OSHA Accident Search page.
Injuries and fatalities could increase over time because of the
increasing number of collaborative and co-existing robots, powered
exoskeletons, and autonomous vehicles into the work environment.
Safety standards are being developed by the Robotic Industries Association (RIA) in conjunction with the American National Standards Institute (ANSI). On October 5, 2017, OSHA, NIOSH and RIA signed an alliance
to work together to enhance technical expertise, identify and help
address potential workplace hazards associated with traditional
industrial robots and the emerging technology of human-robot
collaboration installations and systems, and help identify needed
research to reduce workplace hazards. On October 16 NIOSH launched the Center for Occupational Robotics Research
to "provide scientific leadership to guide the development and use of
occupational robots that enhance worker safety, health, and wellbeing."
So far, the research needs identified by NIOSH and its partners
include: tracking and preventing injuries and fatalities, intervention
and dissemination strategies to promote safe machine control and
maintenance procedures, and on translating effective evidence-based
interventions into workplace practice.
