Autonomous robots are particularly desirable in fields such as spaceflight, household maintenance (such as cleaning), waste water treatment, and delivering goods and services.
Some modern factory robots are "autonomous" within the strict confines of their direct environment. It may not be that every degree of freedom exists in their surrounding environment, but the factory robot's workplace is challenging and can often contain chaotic, unpredicted variables. The exact orientation and position of the next object of work and (in the more advanced factories) even the type of object and the required task must be determined. This can vary unpredictably (at least from the robot's point of view).
One important area of robotics research is to enable the robot to cope with its environment whether this be on land, underwater, in the air, underground, or in space.
A fully autonomous robot can:
Like other machines, autonomous robots still require regular maintenance.
Some modern factory robots are "autonomous" within the strict confines of their direct environment. It may not be that every degree of freedom exists in their surrounding environment, but the factory robot's workplace is challenging and can often contain chaotic, unpredicted variables. The exact orientation and position of the next object of work and (in the more advanced factories) even the type of object and the required task must be determined. This can vary unpredictably (at least from the robot's point of view).
One important area of robotics research is to enable the robot to cope with its environment whether this be on land, underwater, in the air, underground, or in space.
A fully autonomous robot can:
- Gain information about the environment
- Work for an extended period without human intervention
- Move either all or part of itself throughout its operating environment without human assistance
- Avoid situations that are harmful to people, property, or itself unless those are part of its design specifications
Like other machines, autonomous robots still require regular maintenance.
Components and criteria of robotic autonomy
Self-maintenance
The
first requirement for complete physical autonomy is the ability for a
robot to take care of itself. Many of the battery-powered robots on the
market today can find and connect to a charging station, and some toys
like Sony's Aibo are capable of self-docking to charge their batteries.
Self-maintenance is based on "proprioception", or sensing one's
own internal status. In the battery charging example, the robot can tell
proprioceptively that its batteries are low and it then seeks the
charger. Another common proprioceptive sensor is for heat monitoring.
Increased proprioception will be required for robots to work
autonomously near people and in harsh environments. Common
proprioceptive sensors include thermal, optical, and haptic sensing, as
well as the Hall effect (electric).
Robot
GUI display showing battery voltage and other proprioceptive data in
lower right-hand corner. The display is for user information only.
Autonomous robots monitor and respond to proprioceptive sensors without human intervention to keep themselves safe and operating properly.
Sensing the environment
Exteroception
is sensing things about the environment. Autonomous robots must have a
range of environmental sensors to perform their task and stay out of
trouble.
- Common exteroceptive sensors include the electromagnetic spectrum, sound, touch, chemical (smell, odor), temperature, range to various objects, and altitude.
Some robotic lawn mowers will adapt their programming by detecting
the speed in which grass grows as needed to maintain a perfectly cut
lawn, and some vacuum cleaning robots have dirt detectors that sense how
much dirt is being picked up and use this information to tell them to
stay in one area longer.
Task performance
The
next step in autonomous behavior is to actually perform a physical
task. A new area showing commercial promise is domestic robots, with a
flood of small vacuuming robots beginning with iRobot and Electrolux
in 2002. While the level of intelligence is not high in these systems,
they navigate over wide areas and pilot in tight situations around homes
using contact and non-contact sensors. Both of these robots use
proprietary algorithms to increase coverage over simple random bounce.
The next level of autonomous task performance requires a robot to
perform conditional tasks. For instance, security robots can be
programmed to detect intruders and respond in a particular way depending
upon where the intruder is.
For a robot to associate behaviors with a place (localization)
requires it to know where it is and to be able to navigate
point-to-point. Such navigation began with wire-guidance in the 1970s
and progressed in the early 2000s to beacon-based triangulation.
Current commercial robots autonomously navigate based on sensing
natural features. The first commercial robots to achieve this were
Pyxus' HelpMate hospital robot and the CyberMotion guard robot, both
designed by robotics pioneers in the 1980s. These robots originally used
manually created CAD floor plans, sonar sensing and wall-following variations to navigate buildings. The next generation, such as MobileRobots' PatrolBot and autonomous wheelchair,
both introduced in 2004, have the ability to create their own
laser-based maps of a building and to navigate open areas as well as
corridors. Their control system changes its path on the fly if something
blocks the way.
At first, autonomous navigation was based on planar sensors, such
as laser range-finders, that can only sense at one level. The most
advanced systems now fuse information from various sensors for both
localization (position) and navigation. Systems such as Motivity can
rely on different sensors in different areas, depending upon which
provides the most reliable data at the time, and can re-map a building
autonomously.
Rather than climb stairs, which requires highly specialized
hardware, most indoor robots navigate handicapped-accessible areas,
controlling elevators, and electronic doors.
With such electronic access-control interfaces, robots can now freely
navigate indoors. Autonomously climbing stairs and opening doors
manually are topics of research at the current time.
As these indoor techniques continue to develop, vacuuming robots
will gain the ability to clean a specific user-specified room or a whole
floor. Security robots will be able to cooperatively surround intruders
and cut off exits. These advances also bring concomitant protections:
robots' internal maps typically permit "forbidden areas" to be defined
to prevent robots from autonomously entering certain regions.
Outdoor autonomy is most easily achieved in the air, since obstacles are rare. Cruise missiles
are rather dangerous highly autonomous robots. Pilotless drone aircraft
are increasingly used for reconnaissance. Some of these unmanned aerial vehicles
(UAVs) are capable of flying their entire mission without any human
interaction at all except possibly for the landing where a person
intervenes using radio remote control. Some drones are capable of safe,
automatic landings, however. An autonomous ship was announced in
2014—the Autonomous spaceport drone ship—and is scheduled to make its first operational test in December 2014.
Outdoor autonomy is the most difficult for ground vehicles, due to:
- Three-dimensional terrain
- Great disparities in surface density
- Weather exigencies
- Instability of the sensed environment
Open problems in autonomous robotics
There are several open problems in autonomous robotics which are
special to the field rather than being a part of the general pursuit of
AI. According to George A. Bekey's Autonomous Robots: From Biological Inspiration to Implementation and Control, problems include things such as making sure the robot is able to function correctly and not run into obstacles autonomously.
- Energy autonomy and foraging
Researchers concerned with creating true artificial life are concerned not only with intelligent control, but further with the capacity of the robot to find its own resources through foraging (looking for food, which includes both energy and spare parts).
This is related to autonomous foraging, a concern within the sciences of behavioral ecology, social anthropology, and human behavioral ecology; as well as robotics, artificial intelligence, and artificial life.
History and development
The Seekur and MDARS robots demonstrate their autonomous navigation and security capabilities at an airbase.
The Seekur robot was the first commercially available robot to
demonstrate MDARS-like capabilities for general use by airports, utility
plants, corrections facilities and Homeland Security.
The Mars rovers MER-A and MER-B (now known as Spirit rover and Opportunity rover) can find the position of the sun and navigate their own routes to destinations, on the fly, by:
- Mapping the surface with 3D vision
- Computing safe and unsafe areas on the surface within that field of vision
- Computing optimal paths across the safe area towards the desired destination
- Driving along the calculated route;
- Repeating this cycle until either the destination is reached, or there is no known path to the destination
The planned ESA Rover, ExoMars Rover, is capable of vision based
relative localisation and absolute localisation to autonomously navigate
safe and efficient trajectories to targets by:
- Reconstructing 3D models of the terrain surrounding the Rover using a pair of stereo cameras
- Determining safe and unsafe areas of the terrain and the general "difficulty" for the Rover to navigate the terrain
- Computing efficient paths across the safe area towards the desired destination
- Driving the Rover along the planned path
- Building up a navigation map of all previous navigation data
During the final NASA Sample Return Robot Centennial Challenge in
2016, a rover, named Cataglyphis, successfully demonstrated fully
autonomous navigation, decision-making, and sample detection, retrieval,
and return capabilities.
The rover relied on a fusion of measurements from inertial sensors,
wheel encoders, Lidar, and camera for navigation and mapping, instead of
using GPS or magnetometers. During the 2 hour challenge, Cataglyphis
traversed over 2.6 km and returned five different samples to its
starting position.
The DARPA Grand Challenge and DARPA Urban Challenge
have encouraged development of even more autonomous capabilities for
ground vehicles, while this has been the demonstrated goal for aerial
robots since 1990 as part of the AUVSI International Aerial Robotics Competition.
Between 2013 and 2017, Total S.A. has held the ARGOS Challenge
to develop the first autonomous robot for oil and gas production sites.
The robots had to face adverse outdoor conditions such as rain, wind
and extreme temperatures.
Delivery robot
A
delivery robot is an autonomous robot used for delivering goods. As of
February 2017 there were several notable companies developing delivery
robots (some with pilot deliveries in progress):
- Starship Technologies
- Dispatch
- Marble
- Piaggio Fast Forward cargo droid
- Toyota/Pizza Hut e-palette
- Nuro
Research and education mobile robots
Research
and education mobile robots are mainly used during a prototyping phase
in the process of building full scale robots. They are a scaled down
versions of bigger robots with the same types of sensors, kinematics and
software stack (eg. ROS). They are often extendable and provide
comfortable programming interface and development tools. Next to full
scale robot prototyping they are also used for education, especially at
university level, where more and more labs about programming autonomous
vehicles are being introduced. Some of the popular research and
education robots are:
- TurtleBot
- ROSbot 2.0
Legislation
In March 2016, a bill was introduced in Washington, D.C., allowing pilot ground robotic deliveries.
The program was to take place from September 15 through the end of
December 2017. The robots were limited to a weight of 50 pounds unloaded
and a maximum speed of 10 miles per hour. In case the robot stopped
moving because of malfunction the company was required to remove it from
the streets within 24 hours. There were allowed only 5 robots to be
tested per company at a time. A 2017 version of the Personal Delivery Device Act bill was under review as of March 2017.
In February 2017, a bill was passed in the US state of Virginia via the House bill, HB2016, and the Senate bill, SB1207,
that will allow autonomous delivery robots to travel on sidewalks and
use crosswalks statewide beginning on July 1, 2017. The robots will be
limited to a maximum speed of 10 mph and a maximum weight of 50 pounds. In the states of Idaho and Florida there are also talks about passing the similar legislature.
It has been discussed
that robots with similar characteristics to invalid carriages (e.g.
10 mph maximum, limited battery life) might be a workaround for certain
classes of applications. If the robot was sufficiently intelligent and
able to recharge itself using the existing electric vehicle (EV)
charging infrastructure it would only need minimal supervision and a
single arm with low dexterity might be enough to enable this function if
its visual systems had enough resolution.
In November 2017, the San Francisco Board of Supervisors
announced that companies would need to get a city permit in order to
test these robots. In addition, sidewalk delivery robots have been banned from making non-research deliveries.
