Programmable matter

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Programmable_matter

Programmable matter is matter which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion, based upon user input or autonomous sensing. Programmable matter is thus linked to the concept of a material which inherently has the ability to perform information processing.

History

Programmable matter is a term originally coined in 1991 by Toffoli and Margolus to refer to an ensemble of fine-grained computing elements arranged in space. Their paper describes a computing substrate that is composed of fine-grained compute nodes distributed throughout space which communicate using only nearest neighbor interactions. In this context, programmable matter refers to compute models similar to cellular automata and lattice gas automata. The CAM-8 architecture is an example hardware realization of this model. This function is also known as "digital referenced areas" (DRA) in some forms of self-replicating machine science.

In the early 1990s, there was a significant amount of work in reconfigurable modular robotics with a philosophy similar to programmable matter.

As semiconductor technology, nanotechnology, and self-replicating machine technology have advanced, the use of the term programmable matter has changed to reflect the fact that it is possible to build an ensemble of elements which can be "programmed" to change their physical properties in reality, not just in simulation. Thus, programmable matter has come to mean "any bulk substance which can be programmed to change its physical properties."

In the summer of 1998, in a discussion on artificial atoms and programmable matter, Wil McCarthy and G. Snyder coined the term "quantum wellstone" (or simply "wellstone") to describe this hypothetical but plausible form of programmable matter. McCarthy has used the term in his fiction.

In 2002, Seth Goldstein and Todd Mowry started the claytronics project at Carnegie Mellon University to investigate the underlying hardware and software mechanisms necessary to realize programmable matter.

In 2004, the DARPA Information Science and Technology group (ISAT) examined the potential of programmable matter. This resulted in the 2005–2006 study "Realizing Programmable Matter", which laid out a multi-year program for the research and development of programmable matter.

In 2007, programmable matter was the subject of a DARPA research solicitation and subsequent program.

From 2016 to 2022, the ANR has funded several research programs coordinated by Julien Bourgeois and Benoit Piranda at the FEMTO-ST Institute, which is taking the lead in the Claytronics project initiated by Intel and Carnegie Mellon University.

Approaches

In one school of thought the programming could be external to the material and might be achieved by the "application of light, voltage, electric or magnetic fields, etc." (McCarthy 2006). For example, a liquid crystal display is a form of programmable matter. A second school of thought is that the individual units of the ensemble can compute and the result of their computation is a change in the ensemble's physical properties. An example of this more ambitious form of programmable matter is claytronics.

There are many proposed implementations of programmable matter. Scale is one key differentiator between different forms of programmable matter. At one end of the spectrum reconfigurable modular robotics pursues a form of programmable matter where the individual units are in the centimeter size range. At the nanoscale end of the spectrum there are a tremendous number of different bases for programmable matter, ranging from shape changing molecules to quantum dots. Quantum dots are in fact often referred to as artificial atoms. In the micrometer to sub-millimeter range examples include MEMS-based units, cells created using synthetic biology, and the utility fog concept.

An important sub-group of programmable matter are robotic materials, which combine the structural aspects of a composite with the affordances offered by tight integration of sensors, actuators, computation and communication, while foregoing reconfiguration by particle motion.

Examples

There are many conceptions of programmable matter, and thus many discrete avenues of research using the name. Below are some specific examples of programmable matter.

"Solid-liquid phase-change pumping"

Shape-changing and locomotion of solid objects are possible with solid-liquid phase change pumping. This approach allows deforming objects into any intended shape with sub-millimetre resolution and freely changing their topology.

"Simple"

These include materials that can change their properties based on some input, but do not have the ability to do complex computation by themselves.

Complex fluids

Main article: Complex fluids

The physical properties of several complex fluids can be modified by applying a current or voltage, as is the case with liquid crystals.

Metamaterials

Main article: Metamaterials

Metamaterials are artificial composites that can be controlled to react in ways that do not occur in nature. One example developed by David Smith and then by John Pendry and David Schuri is of a material that can have its index of refraction tuned so that it can have a different index of refraction at different points in the material. If tuned properly, this could result in an invisibility cloak.

A further example of programmable -mechanical- metamaterial is presented by Bergamini et al. Here, a pass band within the phononic bandgap is introduced, by exploiting variable stiffness of piezoelectric elements linking aluminum stubs to the aluminum plate to create a phononic crystal as in the work of Wu et al. The piezoelectric elements are shunted to ground over synthetic inductors. Around the resonance frequency of the LC circuit formed by the piezoelectric and the inductors, the piezoelectric elements exhibit near zero stiffness, thus effectively disconnecting the stubs from the plate. This is considered an example of programmable mechanical metamaterial.

In 2021, Chen et al. demonstrated a mechanical metamaterial whose unit cells can each store a binary digit analogous to a bit inside a hard disk drive.milarly, these mechanical unit cells are programmed through the interaction between two electromagnetic coils in the Maxwell configuration, and an embedded magnetorheological elastomer. Different binary states are associated with different stress-strain response of the material.

Shape-changing molecules

An active area of research is in molecules that can change their shape, as well as other properties, in response to external stimuli. These molecules can be used individually or en masse to form new kinds of materials. For example, J Fraser Stoddart's group at UCLA has been developing molecules that can change their electrical properties.

Electropermanent magnets

Main article: Electropermanent magnet

An electropermanent magnet is a type of magnet which consists of both an electromagnet and a dual material permanent magnet, in which the magnetic field produced by the electromagnet is used to change the magnetization of the permanent magnet. The permanent magnet consists of magnetically hard and soft materials, of which only the soft material can have its magnetization changed. When the magnetically soft and hard materials have opposite magnetizations the magnet has no net field, and when they are aligned the magnet displays magnetic behaviour.

They allow creating controllable permanent magnets where the magnetic effect can be maintained without requiring a continuous supply of electrical energy. For these reasons, electropermanent magnets are essential components of the research studies aiming to build programmable magnets that can give rise to self-building structures.

Robotics-based approaches

Self-reconfiguring modular robotics

Main article: Self-reconfiguring modular robot

Self-reconfiguring modular robotics is a field of robotics in which a group of basic robot modules work together to dynamically form shapes and create behaviours suitable for many tasks, similar to programmable matter. SRCMR aims to offer significant improvement to many kinds of objects or systems by introducing many new possibilities. For example: 1. Most important is the incredible flexibility that comes from the ability to change the physical structure and behavior of a solution by changing the software that controls modules. 2. The ability to self-repair by automatically replacing a broken module will make SRCMR solution incredibly resilient. 3. Reducing the environmental footprint by reusing the same modules in many different solutions. Self-reconfiguring modular robotics enjoys a vibrant and active research community.

Claytronics

Claytronics is an emerging field of engineering concerning reconfigurable nanoscale robots ('claytronic atoms', or catoms) designed to form much larger scale machines or mechanisms. The catoms will be sub-millimeter computers that will eventually have the ability to move around, communicate with other computers, change color, and electrostatically connect to other catoms to form different shapes.

Cellular automata

Main article: Cellular automata

Cellular automata are a useful concept to abstract some of the concepts of discrete units interacting to give a desired overall behavior.

Quantum wells

Main article: Quantum well

Quantum wells can hold one or more electrons. Those electrons behave like artificial atoms which, like real atoms, can form covalent bonds, but these are extremely weak. Because of their larger sizes, other properties are also widely different.

Synthetic biology

Main article: Synthetic biology

A ribosome is a biological machine that utilizes protein dynamics on nanoscales to synthesize proteins.

Synthetic biology is a field that aims to engineer cells with "novel biological functions." Such cells are usually used to create larger systems (e.g., biofilms) which can be "programmed" utilizing synthetic gene networks such as genetic toggle switches, to change their color, shape, etc. Such bioinspired approaches to materials production has been demonstrated, using self-assembling bacterial biofilm materials that can be programmed for specific functions, such as substrate adhesion, nanoparticle templating, and protein immobilization.

Microbotics

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Microbotics

Jasmine minirobots each smaller than 3 cm (1 in) in width

Microbotics (or microrobotics) is the field of miniature robotics, in particular mobile robots with characteristic dimensions less than 1 mm. The term can also be used for robots capable of handling micrometer size components.

History

Microbots were born thanks to the appearance of the microcontroller in the last decade of the 20th century, and the appearance of microelectromechanical systems (MEMS) on silicon, although many microbots do not use silicon for mechanical components other than sensors. The earliest research and conceptual design of such small robots was conducted in the early 1970s in (then) classified research for U.S. intelligence agencies. Applications envisioned at that time included prisoner of war rescue assistance and electronic intercept missions. The underlying miniaturization support technologies were not fully developed at that time, so that progress in prototype development was not immediately forthcoming from this early set of calculations and concept design. As of 2008, the smallest microrobots use a scratch drive actuator.

The development of wireless connections, especially Wi-Fi (i.e. in household networks) has greatly increased the communication capacity of microbots, and consequently their ability to coordinate with other microbots to carry out more complex tasks. Indeed, much recent research has focused on microbot communication, including a 1,024 robot swarm at Harvard University that assembles itself into various shapes; and manufacturing microbots at SRI International for DARPA's "MicroFactory for Macro Products" program that can build lightweight, high-strength structures.

Microbots called xenobots have also been built using biological tissues instead of metal and electronics. Xenobots avoid some of the technological and environmental complications of traditional microbots as they are self-powered, biodegradable, and biocompatible.

Definitions

While the "micro" prefix has been used subjectively to mean "small", standardizing on length scales avoids confusion. Thus a nanorobot would have characteristic dimensions at or below 1 micrometer, or manipulate components on the 1 to 1000 nm size range. A microrobot would have characteristic dimensions less than 1 millimeter, a millirobot would have dimensions less than a cm, a mini-robot would have dimensions less than 10 cm (4 in), and a small robot would have dimensions less than 100 cm (39 in).

Many sources also describe robots larger than 1 millimeter as microbots or robots larger than 1 micrometer as nanobots. See also: Category:Micro robots

Design considerations

The way microrobots move around is a function of their purpose and necessary size. At submicron sizes, the physical world demands rather bizarre ways of getting around. The Reynolds number for airborne robots is less than unity; the viscous forces dominate the inertial forces, so “flying” could use the viscosity of air, rather than Bernoulli's principle of lift. Robots moving through fluids may require rotating flagella like the motile form of E. coli. Hopping is stealthy and energy-efficient; it allows the robot to negotiate the surfaces of a variety of terrains. Pioneering calculations (Solem 1994) examined possible behaviors based on physical realities.

One of the major challenges in developing a microrobot is to achieve motion using a very limited power supply. The microrobots can use a small lightweight battery source like a coin cell or can scavenge power from the surrounding environment in the form of vibration or light energy. Microrobots are also now using biological motors as power sources, such as flagellated Serratia marcescens, to draw chemical power from the surrounding fluid to actuate the robotic device. These biorobots can be directly controlled by stimuli such as chemotaxis or galvanotaxis with several control schemes available. A popular alternative to an onboard battery is to power the robots using externally induced power. Examples include the use of electromagnetic fields, ultrasound and light to activate and control micro robots.

The 2022 study focused on a photo-biocatalytic approach for the "design of light-driven microrobots with applications in microbiology and biomedicine".

Types and applications

Due to their small size, microbots are potentially very cheap, and could be used in large numbers (swarm robotics) to explore environments which are too small or too dangerous for people or larger robots. It is expected that microbots will be useful in applications such as looking for survivors in collapsed buildings after an earthquake or crawling through the digestive tract. What microbots lack in brawn or computational power, they can make up for by using large numbers, as in swarms of microbots.

Potential applications with demonstrated prototypes include:

Medical microbots

Biohybrid bacterial microswimmers 

Biohybrid diatomite microswimmer drug delivery system

Diatom frustule surface functionalised with photoactivable molecules (orange spheres) linked to vitamin B-12 (red sphere) acting as a tumor-targeting tag. The system can be loaded with chemotherapeutic drugs (light blue spheres), which can be selectively delivered to colorectal cancer cells. In addition, diatomite microparticles can be photoactivated to generate carbon monoxide or free radicals inducing tumor cell apoptosis.

Biohybrid microswimmers, mainly composed of integrated biological actuators and synthetic cargo carriers, have recently shown promise toward minimally invasive theranostic applications. Various microorganisms, including bacteria, microalgae, and spermatozoids, have been utilised to fabricate different biohybrid microswimmers with advanced medical functionalities, such as autonomous control with environmental stimuli for targeting, navigation through narrow gaps, and accumulation to necrotic regions of tumor environments. Steerability of the synthetic cargo carriers with long-range applied external fields, such as acoustic or magnetic fields, and intrinsic taxis behaviours of the biological actuators toward various environmental stimuli, such as chemoattractants, pH, and oxygen, make biohybrid microswimmers a promising candidate for a broad range of medical active cargo delivery applications.

For example, there are biocompatible microalgae-based microrobots for active drug-delivery in the lungs and the gastrointestinal tract, and magnetically guided engineered bacterial microbots for 'precision targeting' for fighting cancer that all have been tested with mice.

kipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Microbotics

Jasmine minirobots each smaller than 3 cm (1 in) in width

Microbotics (or microrobotics) is the field of miniature robotics, in particular mobile robots with characteristic dimensions less than 1 mm. The term can also be used for robots capable of handling micrometer size components.

History

Microbots were born thanks to the appearance of the microcontroller in the last decade of the 20th century, and the appearance of microelectromechanical systems (MEMS) on silicon, although many microbots do not use silicon for mechanical components other than sensors. The earliest research and conceptual design of such small robots was conducted in the early 1970s in (then) classified research for U.S. intelligence agencies. Applications envisioned at that time included prisoner of war rescue assistance and electronic intercept missions. The underlying miniaturization support technologies were not fully developed at that time, so that progress in prototype development was not immediately forthcoming from this early set of calculations and concept design. As of 2008, the smallest microrobots use a scratch drive actuator.

The development of wireless connections, especially Wi-Fi (i.e. in household networks) has greatly increased the communication capacity of microbots, and consequently their ability to coordinate with other microbots to carry out more complex tasks. Indeed, much recent research has focused on microbot communication, including a 1,024 robot swarm at Harvard University that assembles itself into various shapes; and manufacturing microbots at SRI International for DARPA's "MicroFactory for Macro Products" program that can build lightweight, high-strength structures.

Microbots called xenobots have also been built using biological tissues instead of metal and electronics. Xenobots avoid some of the technological and environmental complications of traditional microbots as they are self-powered, biodegradable, and biocompatible.

Definitions

While the "micro" prefix has been used subjectively to mean "small", standardizing on length scales avoids confusion. Thus a nanorobot would have characteristic dimensions at or below 1 micrometer, or manipulate components on the 1 to 1000 nm size range. A microrobot would have characteristic dimensions less than 1 millimeter, a millirobot would have dimensions less than a cm, a mini-robot would have dimensions less than 10 cm (4 in), and a small robot would have dimensions less than 100 cm (39 in).

Many sources also describe robots larger than 1 millimeter as microbots or robots larger than 1 micrometer as nanobots. See also: Category:Micro robots

Design considerations

The way microrobots move around is a function of their purpose and necessary size. At submicron sizes, the physical world demands rather bizarre ways of getting around. The Reynolds number for airborne robots is less than unity; the viscous forces dominate the inertial forces, so “flying” could use the viscosity of air, rather than Bernoulli's principle of lift. Robots moving through fluids may require rotating flagella like the motile form of E. coli. Hopping is stealthy and energy-efficient; it allows the robot to negotiate the surfaces of a variety of terrains. Pioneering calculations (Solem 1994) examined possible behaviors based on physical realities.

One of the major challenges in developing a microrobot is to achieve motion using a very limited power supply. The microrobots can use a small lightweight battery source like a coin cell or can scavenge power from the surrounding environment in the form of vibration or light energy. Microrobots are also now using biological motors as power sources, such as flagellated Serratia marcescens, to draw chemical power from the surrounding fluid to actuate the robotic device. These biorobots can be directly controlled by stimuli such as chemotaxis or galvanotaxis with several control schemes available. A popular alternative to an onboard battery is to power the robots using externally induced power. Examples include the use of electromagnetic fields, ultrasound and light to activate and control micro robots.

The 2022 study focused on a photo-biocatalytic approach for the "design of light-driven microrobots with applications in microbiology and biomedicine".

Types and applications

Due to their small size, microbots are potentially very cheap, and could be used in large numbers (swarm robotics) to explore environments which are too small or too dangerous for people or larger robots. It is expected that microbots will be useful in applications such as looking for survivors in collapsed buildings after an earthquake or crawling through the digestive tract. What microbots lack in brawn or computational power, they can make up for by using large numbers, as in swarms of microbots.

Potential applications with demonstrated prototypes include:

Medical microbots

Biohybrid bacterial microswimmers 

Biohybrid diatomite microswimmer drug delivery system

Diatom frustule surface functionalised with photoactivable molecules (orange spheres) linked to vitamin B-12 (red sphere) acting as a tumor-targeting tag. The system can be loaded with chemotherapeutic drugs (light blue spheres), which can be selectively delivered to colorectal cancer cells. In addition, diatomite microparticles can be photoactivated to generate carbon monoxide or free radicals inducing tumor cell apoptosis.

Biohybrid microswimmers, mainly composed of integrated biological actuators and synthetic cargo carriers, have recently shown promise toward minimally invasive theranostic applications. Various microorganisms, including bacteria, microalgae, and spermatozoids, have been utilised to fabricate different biohybrid microswimmers with advanced medical functionalities, such as autonomous control with environmental stimuli for targeting, navigation through narrow gaps, and accumulation to necrotic regions of tumor environments. Steerability of the synthetic cargo carriers with long-range applied external fields, such as acoustic or magnetic fields, and intrinsic taxis behaviours of the biological actuators toward various environmental stimuli, such as chemoattractants, pH, and oxygen, make biohybrid microswimmers a promising candidate for a broad range of medical active cargo delivery applications.

For example, there are biocompatible microalgae-based microrobots for active drug-delivery in the lungs and the gastrointestinal tract, and magnetically guided engineered bacterial microbots for 'precision targeting' for fighting cancer that all have been tested with mice.

Robonaut

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Robonaut 

Two Robonaut 2 robots

A robonaut is a humanoid robot, part of a development project conducted by the Dexterous Robotics Laboratory at NASA's Lyndon B. Johnson Space Center (JSC) in Houston, Texas. Robonaut differs from other current space-faring robots in that, while most current space robotic systems (such as robotic arms, cranes and exploration rovers) are designed to move large objects, Robonaut's tasks require more dexterity.

The core idea behind the Robonaut series is to have a humanoid machine work alongside astronauts. Its form factor and dexterity are designed such that Robonaut "is capable of performing all of the tasks required of an EVA-suited crewmember."

NASA states "Robonauts are essential to NASA's future as we go beyond low Earth orbit", and R2 will provide performance data about how a robot may work side-by-side with astronauts.

The latest Robonaut version, R2, was delivered to the International Space Station (ISS) by STS-133 in February 2011. The first US-built robot on the ISS, R2 is a robotic torso designed to assist with crew EVAs and can hold tools used by the crew. However, Robonaut 2 does not have adequate protection needed to exist outside the space station and enhancements and modifications would be required to allow it to move around the station's interior.

As of 2018 NASA planned to return R2 for repairs and then relaunch.

Robonaut 1

Robonaut 1 (R1) was the first model. The two Robonaut versions (R1A and R1B) had many partners including DARPA. None were flown to space. Other designs for Robonaut propose uses for teleoperation on planetary surfaces, where Robonaut could explore a planetary surface while receiving instructions from orbiting astronauts above. Robonaut B was introduced in 2002, R1B is a portable version of R1. R1 had several lower bodies. One of these was the Zero-G Leg, which if Robonaut was working on the space station he would climb using the external handrails and then use his zero-g leg to latch onto the station using a WIF socket. Another was the Robotic Mobility Platform (RMP), developed in 2003, it is a base with two wheels using a Segway PT. And the four wheeled Centaur 1, which was developed in 2006. Robonaut has participated in NASA's Desert Research and Technology Studies field trials in the Arizona desert.

In 2006, the automotive company General Motors expressed interest in the project and proposed to team up with NASA. In 2007 a Space Act Agreement was signed that allowed GM and NASA to work together on the next generation of Robonaut.

• 
  Robonaut with zero-g leg
   
• 
  Robonaut attached to RMP
   
• 
  Robonaut attached to Centaur 1

Robonaut 2

R2 moves for the first time aboard the ISS.

In February 2010, Robonaut 2 (R2) was revealed to the public. R2 is capable of speeds more than four times faster than R1, is more compact, more dexterous, and includes a deeper and wider range of sensing. It can move its arms up to 2 m/s, has a 40 lb payload capacity and its hands have a grasping force of roughly 5 lbs. per finger. There are over 350 sensors and 38 PowerPC processors in the robot.

Station crew members will be able to operate R2, as will controllers on the ground; both will do so using telepresence. One of the improvements over the previous Robonaut generation is that R2 does not need constant supervision. In anticipation of a future destination in which distance and time delays would make continuous management problematic, R2 was designed to be set to tasks and then carry them through autonomously with periodic status checks. While not all human range of motion and sensitivity has been duplicated, the robot's hand has 12 degrees of freedom as well as 2 degrees of freedom in wrist. The R2 model also uses touch sensors at the tips of its fingers.

R2 was designed as a prototype to be used on Earth but mission managers were impressed by R2 and chose to send it to the ISS. Various upgrades were made to qualify it for use inside the station. The outer skin materials were exchanged to meet the station's flammability requirements, shielding was added to reduce electromagnetic interference, processors were upgraded to increase the robot's radiation tolerance, the original fans were replaced with quieter ones to accommodate the station's noise requirements, and the power system was rewired to run on the station's direct current system rather than the alternating current used on the ground.

Robonaut being upgraded on-orbit

In the design of the R2 robot, a 3D time of flight imager will be used in conjunction with a stereo camera pair to provide depth information and visible stereo images to the system. This allows the R2 to "see", which is one of the basic preconditions to fulfill its tasks. To integrate the various sensor data types in a single development environment the image processing software Halcon 9.0 from MVTec Software (Munich, Germany) is used.

2011 Testing at the ISS

Robonaut 2 was launched on STS-133 on February 24, 2011, and delivered to the ISS. On August 22, R2 was powered up for the first time while in low earth orbit. This was called a "power soak" which is a power system test only with no movement. On October 13, R2 moved for the first time while in space. The conditions aboard the space station provide a proving ground for robots to work shoulder to shoulder with people in microgravity. Once this has been demonstrated inside the station, software upgrades and lower bodies may be added, allowing R2 to move around the interior of the station and perform maintenance tasks, such as vacuuming or cleaning filters. A pair of legs were delivered to the ISS on SpX-3 in April 2014. The battery backpack was planned to be launched on a later flight in Summer/Fall 2014.

Further upgrades could be added to allow R2 to work outside in the vacuum of space, where R2 could help space walkers perform repairs, make additions to the station or conduct scientific experiments. There were initially no plans to return the launched R2 back to earth.

2018 Repair and possible relaunch

NASA announced on 1 April 2018 that R2 would return to Earth in May 2018 with CRS-14 Dragon for repair and eventual relaunch in about a year's time. As of 2018 NASA planned to return R2 for repairs and then relaunch.

NASA's experience with R2 on the station will help them understand its capabilities for possible deep space missions.

• 
  R2 aboard ISS with Dan Burbank
   
• 
  R2 attached to Centaur 2
   
• 
  R2 with proposed terrestrial legs
   
• 
  R2 with its 'climbing legs'

Project M (R2 on the moon)

In late 2009, a proposed mission called Project M was announced by Johnson Space Center that, if it had been approved, would have had the objective of landing an R2 robot on the Moon within 1,000 days.

Mechatronics

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Mechatronics 

Mechatronics

Occupation
Names	Mechatronics Engineer
Occupation type	Engineering
Activity sectors	Electrical and mechanical industry, engineering industry
Specialty	Mechanical engineering, electrical/electronics engineering, computer engineering, software programming, system engineering, control system, smart and intelligent system, automation and robotics
Description
Competencies	Multidisciplinary technical knowledge, electro-mechanical system design, system integration and maintenance
Fields of employment	Science, technology, engineering, industry, computer, exploration

Mechatronics engineering, also called mechatronics, is an interdisciplinary branch of engineering that focuses on the integration of mechanical engineering, electrical engineering, electronic engineering and software engineering, and also includes a combination of robotics, computer science, telecommunications, systems, control, and product engineering.

As technology advances over time, various subfields of engineering have succeeded in both adapting and multiplying. The intention of mechatronics is to produce a design solution that unifies each of these various subfields. Originally, the field of mechatronics was intended to be nothing more than a combination of mechanics, electrical and electronics, hence the name being a portmanteau of the words "mechanics" and "electronics"; however, as the complexity of technical systems continued to evolve, the definition had been broadened to include more technical areas.

The word mechatronics originated in Japanese-English and was created by Tetsuro Mori, an engineer of Yaskawa Electric Corporation. The word mechatronics was registered as trademark by the company in Japan with the registration number of "46-32714" in 1971. The company later released the right to use the word to the public, and the word began being used globally. Currently the word is translated into many languages and is considered an essential term for advanced automated industry.

Many people treat mechatronics as a modern buzzword synonymous with automation, robotics and electromechanical engineering.

French standard NF E 01-010 gives the following definition: "approach aiming at the synergistic integration of mechanics, electronics, control theory, and computer science within product design and manufacturing, in order to improve and/or optimize its functionality".

History

The word mechatronics was registered as trademark by the company in Japan with the registration number of "46-32714" in 1971. The company later released the right to use the word to the public, and the word began being used globally.

With the advent of information technology in the 1980s, microprocessors were introduced into mechanical systems, improving performance significantly. By the 1990s, advances in computational intelligence were applied to mechatronics in ways that revolutionized the field.

Description

Aerial Euler diagram from RPI's website describes the fields that make up mechatronics.

A mechatronics engineer unites the principles of mechanics, electrical, electronics, and computing to generate a simpler, more economical and reliable system.

Engineering cybernetics deals with the question of control engineering of mechatronic systems. It is used to control or regulate such a system (see control theory). Through collaboration, the mechatronic modules perform the production goals and inherit flexible and agile manufacturing properties in the production scheme. Modern production equipment consists of mechatronic modules that are integrated according to a control architecture. The most known architectures involve hierarchy, polyarchy, heterarchy, and hybrid. The methods for achieving a technical effect are described by control algorithms, which might or might not utilize formal methods in their design. Hybrid systems important to mechatronics include production systems, synergy drives, exploration rovers, automotive subsystems such as anti-lock braking systems and spin-assist, and everyday equipment such as autofocus cameras, video, hard disks, CD players and phones.

Subdisciplines

Mechanical

Main article: Mechanical engineering

View of the Volkswagen dual clutch direct shift gearbox transmission

Mechanical engineering is an important part of mechatronics engineering. It includes the study of mechanical nature of how an object works. Mechanical elements refer to mechanical structure, mechanism, thermo-fluid, and hydraulic aspects of a mechatronics system. The study of thermodynamics, dynamics, fluid mechanics, pneumatics and hydraulics. Mechatronics engineer who works a mechanical engineer can specialize in hydraulics and pneumatics systems, where they can be found working in automobile industries. A mechatronics engineer can also design a vehicle since they have strong mechanical and electronical background. Knowledge of software applications such as computer-aided design and computer aided manufacturing is essential for designing products. Mechatronics covers a part of mechanical syllabus which is widely applied in automobile industry.

Mechatronic systems represent a large part of the functions of an automobile. The control loop formed by sensor—information processing—actuator—mechanical (physical) change is found in many systems. The system size can be very different. The Anti-lock braking system (ABS) is a mechatronic system. The brake itself is also one. And the control loop formed by driving control (for example cruise control), engine, vehicle driving speed in the real world and speed measurement is a mechatronic system, too. The great importance of mechatronics for automotive engineering is also evident from the fact that vehicle manufacturers often have development departments with "Mechatronics" in their names.

Electronics and Electricals

Main article: Electronics and Electrical Engineering

Electronics and Telecommunication engineering specializes in electronics devices and telecom devices of a mechatronics system. A mechatronics engineer specialized in electronics and telecommunications have knowledge of computer hardware devices. The transmission of signal is the main application of this subfield of mechatronics. Where digital and analog systems also forms an important part of mechatronics systems. Telecommunications engineering deals with the transmission of information across a medium.

Electronics engineering is related to computer engineering and electrical engineering. Control engineering has a wide range of electronic applications from the flight and propulsion systems of commercial airplanes to the cruise control present in many modern cars. VLSI designing is important for creating integrated circuits. Mechatronics engineers have deep knowledge of microprocessors, microcontrollers, microchips and semiconductors. The application of mechatronics in electronics manufacturing industry can conduct research and development on consumer electronic devices such as mobile phones, computers, cameras etc. For mechatronics engineers it is necessary to learn operating computer applications such as MATLAB and Simulink for designing and developing electronic products.

Mechatronics engineering is a interdisciplinary course, it includes concepts of both electrical and mechanical systems. A mechatronics engineer engages in designing high power transformers or radio-frequency module transmitters.

Avionics

Main article: Avionics

An avionics technician uses an oscilloscope to verify signals on aircraft avionics equipment.

Avionics is also considered a variant of mechatronics as it combines several fields such as electronics and telecom with Aerospace engineering. It is the subdiscipline of mechatronics engineering and aerospace engineering which is engineering branch focusing on electronics systems of aircraft. The word avionics is a blend of aviation and electronics. The electronics system of aircraft includes aircraft communication addressing and reporting system, air navigation, aircraft flight control system, aircraft collision avoidance systems, flight recorder, weather radar and lightning detector. These can be as simple as a searchlight for a police helicopter or as complicated as the tactical system for an airborne early warning platform.

Advanced Mechatronics

Main article: Mechatronics

Another variant is Motion control for Advanced Mechatronics, presently recognized as a key technology in mechatronics. The robustness of motion control will be represented as a function of stiffness and a basis for practical realization. Target of motion is parameterized by control stiffness which could be variable according to the task reference. The system robustness of motion always requires very high stiffness in the controller.

Industrial

Main article: Industrial engineering

Industrial engineers on their duty

The branch of industrial engineer includes the design of machinery, assembly and process lines of various manufacturing industries. This branch can be said somewhat similar to automation and robotics. Mechatronics engineers who works as industrial engineers design and develop infrastructure of a manufacturing plant. Also it can be said that they are architect of machines. One can work as an industrial designer to design the industrial layout and plan for setting up of a manufacturing industry or as an industrial technician to lookover the technical requirements and repairing of the particular factory.

Robotics

Main article: Robotics

An industrial robot manufactured by ABB

Robotics is one of the newest emerging subfield of mechatronics. It is the study of robots that how they are manufactured and operated. Since 2000, this branch of mechatronics is attracting a number of aspirants. Robotics is interrelated with automation because here also not much human intervention is required. A large number of factories especially in automobile factories, robots are founds in assembly lines where they perform the job of drilling, installation and fitting. Programming skills are necessary for specialization in robotics. Knowledge of programming language —ROBOTC is important for functioning robots. An industrial robot is a prime example of a mechatronics system; it includes aspects of electronics, mechanics, and computing to do its day-to-day jobs.

Computer

Main articles: Computer engineering and Internet of things

Telescope automatic control system and a space object observation system

The Internet of things (IoT) is the inter-networking of physical devices, embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data. IoT and mechatronics are complementary. Many of the smart components associated with the Internet of Things will be essentially mechatronic. The development of the IoT is forcing mechatronics engineers, designers, practitioners and educators to research the ways in which mechatronic systems and components are perceived, designed and manufactured. This allows them to face up to new issues such as data security, machine ethics and the human-machine interface.

Knowledge of programming is very important. A mechatronics engineer has to do programming in different levels example.—PLC programming, drone programming, hardware programming, CNC programming etc. Due to combination of electronics engineering, soft skills from computer side is important. Important programming languages for mechatronics engineer to learn is Java, Python, C++ and C programming language.

Superintelligence

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Superintelligence

A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. "Superintelligence" may also refer to a property of problem-solving systems (e.g., superintelligent language translators or engineering assistants) whether or not these high-level intellectual competencies are embodied in agents that act in the world. A superintelligence may or may not be created by an intelligence explosion and associated with a technological singularity.

University of Oxford philosopher Nick Bostrom defines superintelligence as "any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest". The program Fritz falls short of this conception of superintelligence—even though it is much better than humans at chess—because Fritz cannot outperform humans in other tasks. Following Hutter and Legg, Bostrom treats superintelligence as general dominance at goal-oriented behavior, leaving open whether an artificial or human superintelligence would possess capacities such as intentionality (cf. the Chinese room argument) or first-person consciousness (cf. the hard problem of consciousness).

Technological researchers disagree about how likely present-day human intelligence is to be surpassed. Some argue that advances in artificial intelligence (AI) will probably result in general reasoning systems that lack human cognitive limitations. Others believe that humans will evolve or directly modify their biology so as to achieve radically greater intelligence. A number of futures studies scenarios combine elements from both of these possibilities, suggesting that humans are likely to interface with computers, or upload their minds to computers, in a way that enables substantial intelligence amplification.

Some researchers believe that superintelligence will likely follow shortly after the development of artificial general intelligence. The first generally intelligent machines are likely to immediately hold an enormous advantage in at least some forms of mental capability, including the capacity of perfect recall, a vastly superior knowledge base, and the ability to multitask in ways not possible to biological entities. This may give them the opportunity to—either as a single being or as a new species—become much more powerful than humans, and to displace them.

A number of scientists and forecasters argue for prioritizing early research into the possible benefits and risks of human and machine cognitive enhancement, because of the potential social impact of such technologies.

Feasibility of artificial superintelligence

Progress in machine classification of images

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The error rate of AI by year. The red line represents the error rate of a trained human.

Philosopher David Chalmers argues that artificial general intelligence is a very likely path to superhuman intelligence. Chalmers breaks this claim down into an argument that AI can achieve equivalence to human intelligence, that it can be extended to surpass human intelligence, and that it can be further amplified to completely dominate humans across arbitrary tasks.

Concerning human-level equivalence, Chalmers argues that the human brain is a mechanical system, and therefore ought to be emulatable by synthetic materials. He also notes that human intelligence was able to biologically evolve, making it more likely that human engineers will be able to recapitulate this invention. Evolutionary algorithms in particular should be able to produce human-level AI. Concerning intelligence extension and amplification, Chalmers argues that new AI technologies can generally be improved on, and that this is particularly likely when the invention can assist in designing new technologies.

An AI system capable of self-improvement could enhance its own intelligence, thereby becoming more efficient at improving itself. This cycle of "recursive self-improvement" might cause an intelligence explosion, resulting in the creation of a superintelligence.

Computer components already greatly surpass human performance in speed. Bostrom writes, "Biological neurons operate at a peak speed of about 200 Hz, a full seven orders of magnitude slower than a modern microprocessor (~2 GHz)." Moreover, neurons transmit spike signals across axons at no greater than 120 m/s, "whereas existing electronic processing cores can communicate optically at the speed of light". Thus, the simplest example of a superintelligence may be an emulated human mind run on much faster hardware than the brain. A human-like reasoner that could think millions of times faster than current humans would have a dominant advantage in most reasoning tasks, particularly ones that require haste or long strings of actions.

Another advantage of computers is modularity, that is, their size or computational capacity can be increased. A non-human (or modified human) brain could become much larger than a present-day human brain, like many supercomputers. Bostrom also raises the possibility of collective superintelligence: a large enough number of separate reasoning systems, if they communicated and coordinated well enough, could act in aggregate with far greater capabilities than any sub-agent.

There may also be ways to qualitatively improve on human reasoning and decision-making. Humans outperform non-human animals in large part because of new or enhanced reasoning capacities, such as long-term planning and language use. (See evolution of human intelligence and primate cognition.) If there are other possible improvements to reasoning that would have a similarly large impact, this makes it likelier that an agent can be built that outperforms humans in the same fashion humans outperform chimpanzees.

All of the above advantages hold for artificial superintelligence, but it is not clear how many hold for biological superintelligence. Physiological constraints limit the speed and size of biological brains in many ways that are inapplicable to machine intelligence. As such, writers on superintelligence have devoted much more attention to superintelligent AI scenarios.

Feasibility of biological superintelligence

Carl Sagan suggested that the advent of Caesarean sections and in vitro fertilization may permit humans to evolve larger heads, resulting in improvements via natural selection in the heritable component of human intelligence. By contrast, Gerald Crabtree has argued that decreased selection pressure is resulting in a slow, centuries-long reduction in human intelligence, and that this process instead is likely to continue into the future. There is no scientific consensus concerning either possibility, and in both cases the biological change would be slow, especially relative to rates of cultural change.

Selective breeding, nootropics, epigenetic modulation, and genetic engineering could improve human intelligence more rapidly. Bostrom writes that if we come to understand the genetic component of intelligence, pre-implantation genetic diagnosis could be used to select for embryos with as much as 4 points of IQ gain (if one embryo is selected out of two), or with larger gains (e.g., up to 24.3 IQ points gained if one embryo is selected out of 1000). If this process is iterated over many generations, the gains could be an order of magnitude greater. Bostrom suggests that deriving new gametes from embryonic stem cells could be used to iterate the selection process very rapidly. This notion, Iterated Embryo Selection, has received wide treatment from other authors. A well-organized society of high-intelligence humans of this sort could potentially achieve collective superintelligence.

Alternatively, collective intelligence might be constructible by better organizing humans at present levels of individual intelligence. A number of writers have suggested that human civilization, or some aspect of it (e.g., the Internet, or the economy), is coming to function like a global brain with capacities far exceeding its component agents. If this systems-based superintelligence relies heavily on artificial components, however, it may qualify as an AI rather than as a biology-based superorganism. A prediction market is sometimes considered an example of working collective intelligence system, consisting of humans only (assuming algorithms are not used to inform decisions).

A final method of intelligence amplification would be to directly enhance individual humans, as opposed to enhancing their social or reproductive dynamics. This could be achieved using nootropics, somatic gene therapy, or brain–computer interfaces. However, Bostrom expresses skepticism about the scalability of the first two approaches, and argues that designing a superintelligent cyborg interface is an AI-complete problem.

Forecasts

Most surveyed AI researchers expect machines to eventually be able to rival humans in intelligence, though there is little consensus on when this will likely happen. At the 2006 AI@50 conference, 18% of attendees reported expecting machines to be able "to simulate learning and every other aspect of human intelligence" by 2056; 41% of attendees expected this to happen sometime after 2056; and 41% expected machines to never reach that milestone.

In a survey of the 100 most cited authors in AI (as of May 2013, according to Microsoft academic search), the median year by which respondents expected machines "that can carry out most human professions at least as well as a typical human" (assuming no global catastrophe occurs) with 10% confidence is 2024 (mean 2034, st. dev. 33 years), with 50% confidence is 2050 (mean 2072, st. dev. 110 years), and with 90% confidence is 2070 (mean 2168, st. dev. 342 years). These estimates exclude the 1.2% of respondents who said no year would ever reach 10% confidence, the 4.1% who said 'never' for 50% confidence, and the 16.5% who said 'never' for 90% confidence. Respondents assigned a median 50% probability to the possibility that machine superintelligence will be invented within 30 years of the invention of approximately human-level machine intelligence.

In a 2022 survey, the median year by which respondents expected "High-level machine intelligence" with 50% confidence is 2061. The survey defined the achievement of high-level machine intelligence as when unaided machines can accomplish every task better and more cheaply than human workers.

In 2023, OpenAI leaders published recommendations for the governance of superintelligence, which they believe may happen in less than 10 years.

Design considerations

Bostrom expressed concern about what values a superintelligence should be designed to have. He compared several proposals:

• The coherent extrapolated volition (CEV) proposal is that it should have the values upon which humans would converge.
• The moral rightness (MR) proposal is that it should value moral rightness.
• The moral permissibility (MP) proposal is that it should value staying within the bounds of moral permissibility (and otherwise have CEV values).

Bostrom clarifies these terms:

instead of implementing humanity's coherent extrapolated volition, one could try to build an AI with the goal of doing what is morally right, relying on the AI's superior cognitive capacities to figure out just which actions fit that description. We can call this proposal "moral rightness" (MR) ... MR would also appear to have some disadvantages. It relies on the notion of "morally right," a notoriously difficult concept, one with which philosophers have grappled since antiquity without yet attaining consensus as to its analysis. Picking an erroneous explication of "moral rightness" could result in outcomes that would be morally very wrong ... The path to endowing an AI with any of these [moral] concepts might involve giving it general linguistic ability (comparable, at least, to that of a normal human adult). Such a general ability to understand natural language could then be used to understand what is meant by "morally right." If the AI could grasp the meaning, it could search for actions that fit ...

One might try to preserve the basic idea of the MR model while reducing its demandingness by focusing on moral permissibility: the idea being that we could let the AI pursue humanity's CEV so long as it did not act in ways that are morally impermissible.

Potential threat to humanity

Main articles: Existential risk from artificial general intelligence, AI alignment, and AI safety

It has been suggested that if AI systems rapidly become superintelligent, they may take unforeseen actions or out-compete humanity. Researchers have argued that, by way of an "intelligence explosion," a self-improving AI could become so powerful as to be unstoppable by humans.

Concerning human extinction scenarios, Bostrom (2002) identifies superintelligence as a possible cause:

When we create the first superintelligent entity, we might make a mistake and give it goals that lead it to annihilate humankind, assuming its enormous intellectual advantage gives it the power to do so. For example, we could mistakenly elevate a subgoal to the status of a supergoal. We tell it to solve a mathematical problem, and it complies by turning all the matter in the solar system into a giant calculating device, in the process killing the person who asked the question.

In theory, since a superintelligent AI would be able to bring about almost any possible outcome and to thwart any attempt to prevent the implementation of its goals, many uncontrolled, unintended consequences could arise. It could kill off all other agents, persuade them to change their behavior, or block their attempts at interference. Eliezer Yudkowsky illustrates such instrumental convergence as follows: "The AI does not hate you, nor does it love you, but you are made out of atoms which it can use for something else."

This presents the AI control problem: how to build an intelligent agent that will aid its creators, while avoiding inadvertently building a superintelligence that will harm its creators. The danger of not designing control right "the first time" is that a superintelligence may be able to seize power over its environment and prevent humans from shutting it down, in order to accomplish its goals. Potential AI control strategies include "capability control" (limiting an AI's ability to influence the world) and "motivational control" (building an AI whose goals are aligned with human values).