Robotic materials

Last updated

Robotic materials are composite materials that combine sensing, actuation, computation, and communication in a repeatable or amorphous pattern. [1] Robotic materials can be considered computational metamaterials in that they extend the original definition of a metamaterial [2] as "macroscopic composites having a man-made, three-dimensional, periodic cellular architecture designed to produce an optimized combination, not available in nature, of two or more responses to specific excitation" by being fully programmable. That is, unlike in a conventional metamaterial, the relationship between a specific excitation and response is governed by sensing, actuation, and a computer program that implements the desired logic. [1]

Contents

History

The idea of creating materials that embed computation is closely related to the concept of programmable matter, a term coined in 1991 [3] by Toffoli and Margolus, describing dense arrays of computing elements that could solve complex finite-element like simulations of material systems, and then later developed to describe a class of materials consisting of identical, mobile building blocks, also known as catoms that are fully reconfigurable, therefore allowing materials to arbitrarily change their physical properties.

Robotic materials build up on the original concept of programmable matter, [3] but focus on the structural properties of the embedding polymers without claim of universal property changes. Here the term "robotic" refers to the confluence of sensing, actuation, and computation, and was coined by Nikolaus Correll and his students in the Science article "Materials that couple sensing, actuation, and computation". [1]

Applications

Robotic materials allow to off-load computation inside the material, most notably signal processing that arises during high-bandwidth sensing applications or feedback control that is required by fine-grained distributed actuation. Examples for such applications include camouflage, shape change, load balancing, and robotic skins [4] as well as equipping robots with more autonomy by off-loading some of the signal processing and controls into the material, [5] creating "materials that make robots smart" [6]

Research challenges

Research in robotic materials ranges from the device-level and manufacturing to the distributed algorithms that equip robotic materials with intelligence. [7] As such it intersects the fields of composite materials, sensor networks, distributed algorithms, and due to the scale of the involved computation, swarm intelligence. Unlike any individual field, the design of the structure, sensors, actuators, communication infrastructure, and distributed algorithms are tightly intertwined. For example, the material properties of the structural material will affect how signals to be sensed propagate through the material, at which distance computational elements need to be spaced, and what signal processing needs to be done. Similarly, structural properties are closely related to the actual embedding of computing and communication infrastructure. Capturing these effects therefore requires interdisciplinary collaboration between materials, computer science, and robotics. [1] From a material science perspective, a particular challenge lies in materials that enable the instant creation of complex objects and their transfiguration on command. An overview of different approaches for such materials is provided by Kaya et al. [8]

Related Research Articles

Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers.

<span class="mw-page-title-main">Theoretical computer science</span> Subfield of computer science and mathematics

Theoretical computer science is a subfield of computer science and mathematics that focuses on the abstract and mathematical foundations of computation.

<span class="mw-page-title-main">Computer science and engineering</span> University academic program

Computer science and engineering (CSE) or Computer Science (CS) also integrated as Electrical engineering and Computer Science (EECS) in some universities, is an academic program at many universities which comprises approaches of computer science and computer engineering. There is no clear division in computing between science and engineering, just like in the field of materials science and engineering. However, some classes are historically more related to computer science, and other to computer engineering. CSE is also a term often used in Europe to translate the name of technical or engineering informatics academic programs. It is offered in both undergraduate as well postgraduate with specializations.

Quantum Information Science is a field that combines the principles of quantum mechanics with information theory to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. The term quantum information theory is sometimes used, but it does not include experimental research and can be confused with a subfield of quantum information science that deals with the processing of quantum information.

Computronium is a material hypothesized by Norman Margolus and Tommaso Toffoli of MIT in 1991 to be used as "programmable matter", a substrate for computer modeling of virtually any real object.

<span class="mw-page-title-main">Block cellular automaton</span> Kind of cellular automaton

A block cellular automaton or partitioning cellular automaton is a special kind of cellular automaton in which the lattice of cells is divided into non-overlapping blocks and the transition rule is applied to a whole block at a time rather than a single cell. Block cellular automata are useful for simulations of physical quantities, because it is straightforward to choose transition rules that obey physical constraints such as reversibility and conservation laws.

Unconventional computing is computing by any of a wide range of new or unusual methods.

Modular self-reconfiguring robotic systems or self-reconfigurable modular robots are autonomous kinematic machines with variable morphology. Beyond conventional actuation, sensing and control typically found in fixed-morphology robots, self-reconfiguring robots are also able to deliberately change their own shape by rearranging the connectivity of their parts, in order to adapt to new circumstances, perform new tasks, or recover from damage.

Programmable matter is matter which has the ability to change its physical properties 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.

Amorphous computing refers to computational systems that use very large numbers of identical, parallel processors each having limited computational ability and local interactions. The term amorphous computing was coined at MIT in 1996 in a paper entitled "Amorphous Computing Manifesto" by Abelson, Knight, Sussman, et al.

Natural computing, also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials to compute. The main fields of research that compose these three branches are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others.

Norman H. Margolus is a Canadian-American physicist and computer scientist, known for his work on cellular automata and reversible computing. He is a research affiliate with the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology.

<span class="mw-page-title-main">Reversible cellular automaton</span> Cellular automaton that can be run backwards

A reversible cellular automaton is a cellular automaton in which every configuration has a unique predecessor. That is, it is a regular grid of cells, each containing a state drawn from a finite set of states, with a rule for updating all cells simultaneously based on the states of their neighbors, such that the previous state of any cell before an update can be determined uniquely from the updated states of all the cells. The time-reversed dynamics of a reversible cellular automaton can always be described by another cellular automaton rule, possibly on a much larger neighborhood.

Robotic sensing is a subarea of robotics science intended to provide sensing capabilities to robots. Robotic sensing provides robots with the ability to sense their environments and is typically used as feedback to enable robots to adjust their behavior based on sensed input. Robot sensing includes the ability to see, touch, hear and move and associated algorithms to process and make use of environmental feedback and sensory data. Robot sensing is important in applications such as vehicular automation, robotic prosthetics, and for industrial, medical, entertainment and educational robots.

Mechanical metamaterials are rationally designed artificial materials/structures of precision geometrical arrangements leading to unusual physical and mechanical properties. These unprecedented properties are often derived from their unique internal structures rather than the materials from which they are made. Inspiration for mechanical metamaterials design often comes from biological materials, from molecular and crystalline unit cell structures as well as the artistic fields of origami and kirigami. While early mechanical metamaterials had regular repeats of simple unit cell structures, increasingly complex units and architectures are now being explored. Mechanical metamaterials can be seen as a counterpart to the rather well-known family of optical metamaterials and electromagnetic metamaterials. Mechanical properties, including elasticity, viscoelasticity, and thermoelasticity, are central to the design of mechanical metamaterials. They are often also referred to as elastic metamaterials or elastodynamic metamaterials. Their mechanical properties can be designed to have values that cannot be found in nature, such as negative stiffness, negative Poisson’s ratio, negative compressibility, and vanishing shear modulus.

The Rice University Department of Electrical and Computer Engineering is one of nine academic departments at the George R. Brown School of Engineering at Rice University. Ashutosh Sabharwal is the Department Chair. Originally the Rice Department of Electrical Engineering, it was renamed in 1984 to Electrical and Computer Engineering.

<span class="mw-page-title-main">Nikolaus Correll</span>

Nikolaus Correll is a roboticist and an associate professor at the University of Colorado at Boulder in the Department of Computer Science with courtesy appointments in the departments of Aerospace, Electrical and Materials Engineering. Nikolaus is the faculty director of the Interdisciplinary Research Theme on Multi-functional Materials at the College of Engineering and Applied Science, and the founder and CTO of Robotic Materials Inc.

<span class="mw-page-title-main">Soft robotics</span> Subfield of robotics

Soft robotics is a subfield of robotics that concerns the design, control, and fabrication of robots composed of compliant materials, instead of rigid links. In contrast to rigid-bodied robots built from metals, ceramics and hard plastics, the compliance of soft robots can improve their safety when working in close contact with humans.

<span class="mw-page-title-main">Alper Erturk</span>

Alper Erturk is a mechanical engineer and the Woodruff Professor in the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology.

This glossary of computer science is a list of definitions of terms and concepts used in computer science, its sub-disciplines, and related fields, including terms relevant to software, data science, and computer programming.

References

  1. 1 2 3 4 M. A. McEvoy and N.Correll. Materials that couple sensing, actuation, computation, and communication, Science Vol. 347 no. 6228 DOI: 10.1126/science.1261689
  2. ↑ R. M. Walser, Electromagnetic metamaterials. Proc. SPIE 4467, Complex Mediums II: Beyond Linear Isotropic Dielectrics (San Diego, CA, 2001), pp. 1–15 (2001).
  3. 1 2 T. Toffoli, N. Margolus, Programmable matter: Concepts and realization. Physica D 47, 263–272 (1991). 10.1016/0167-2789(91)90296
  4. ↑ Robotic materials: Changing with the world around them, phys.org, March 19, 2015.
  5. ↑ Autonomous Materials will let future robots change color and shift shape, Popular Science, March 19, 2015.
  6. ↑ Hughes, Dana (2019). "Materials that make robots smart". International Journal of Robotics Research. 38 (12–13): 1338–1351. arXiv: 1711.00537 . doi: 10.1177/0278364919856099 .
  7. ↑ Materials that Couple Sensing, Actuation, Computation and Communication, Computing Community Consortium (CCC) "Great Innovative Ideas", November 2, 2015.
  8. ↑ Kaya, Kerem; Kravchenko, Alexander; Scarpellini, Claudia; Iseri, Emre; Kragic, Danica; van der Wijngaart, Wouter (2023). "Programmable Matter with Free and High-Resolution Transfiguration and Locomotion". Advanced Functional Materials. 34 (14). doi: 10.1002/adfm.202307105 .
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.