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Swarm robotics

Swarm robotics
Swarm of open-source Jasmine micro-robots recharging themselves Swarm robotics is a new approach to the coordination of multirobot systems which consist of large numbers of mostly simple physical robots. It is supposed that a desired collective behavior emerges from the interactions between the robots and interactions of robots with the environment. This approach emerged on the field of artificial swarm intelligence, as well as the biological studies of insects, ants and other fields in nature, where swarm behaviour occurs. Definition[edit] The research of swarm robotics is to study the design of robots, their physical body and their controlling behaviors. Unlike distributed robotic systems in general, swarm robotics emphasizes a large number of robots, and promotes scalability, for instance by using only local communication. Video tracking is an essential tool for systematically studying swarm-behavior, even though other tracking methods are available. Goals and applications[edit] Related:  SWARM BEHAVIOURmangouste66

Ant robotics Ant robotics is a special case of swarm robotics. Swarm robots are simple (and hopefully, therefore cheap) robots with limited sensing and computational capabilities. This makes it feasible to deploy teams of swarm robots and take advantage of the resulting fault tolerance and parallelism. Invention[edit] In 1991, American electrical engineer James McLurkin was the first to conceptualize the idea of "robot ants" while working at the MIT Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Background[edit] Researchers have developed ant robot hardware and software and demonstrated, both in simulation and on physical robots, that single ant robots or teams of ant robots solve robot-navigation tasks (such as path following[4] and terrain coverage[1][6]) robustly and efficiently. See also[edit] References[edit] ^ Jump up to: a b J. External links[edit] Ant robot by Sven KoenigAnt algorithm by Israel Wagner

Swarmanoid project Distributed Robotics Emergence Snowflakes forming complex symmetrical patterns is an example of emergence in a physical system. In philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. Emergence is central to the theories of integrative levels and of complex systems. Biology can be viewed as an emergent property of the laws of chemistry which, in turn, can be viewed as an emergent property of particle physics. Similarly, psychology could be understood as an emergent property of neurobiological dynamics, and free-market theories understand economy as an emergent feature of psychology. Definitions[edit] The idea of emergence has been around since at least the time of Aristotle. The term "emergent" was coined by philosopher G. Goldstein's definition can be further elaborated to describe the qualities of this definition in more detail: Rules, or laws, have no causal efficacy; they do not in fact “generate” anything.

Slime mould used to create first robot run by living cells | Science Ever worried that the terrifying cyborgs that fill sci-fi stories might one day become a reality? Perhaps the latest research by Klaus-Peter Zauner of Southampton University will cause a stir: the engineer has invented a robot that is controlled by living cells. The cells in question are a specially grown type of "slime mould" that naturally shies away from light. Dr Zauner grew a star-shaped sample of the slime mould and attached it to a six-legged robot (with each point of the star attached to a leg) to control its movements. Shining white light on to a section of the single cell organism made it vibrate, changing its thickness. The work came out of a collaboration with scientists at Kobe University in Japan, who had been studying ways of using biological cells in robots. "The long-term vision that I have is that this technology we're after is going to be somewhere between living cells and molecules," he said. Using biological cells provides some autonomy to the robot's movements.

Swarm intelligence Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.[1] The application of swarm principles to robots is called swarm robotics, while 'swarm intelligence' refers to the more general set of algorithms. Example algorithms[edit] Particle swarm optimization[edit] Ant colony optimization[edit] Artificial bee colony algorithm[edit] Artificial bee colony algorithm (ABC) is a meta-heuristic algorithm introduced by Karaboga in 2005,[5] and simulates the foraging behaviour of honey bees. Bacterial colony optimization[edit] The algorithm is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration.[6] Differential evolution[edit]

Swarmrobot | Open-source micro-robotic project James McLurkin's Personal Webpage What is a "Swarm"? As robots become more and more useful, multiple robots working together on a single task will become commonplace. Many of the most useful applications of robots are particularly well-suited to this "swarm" approach. Groups of robots can perform these tasks more efficiently, and can perform them in fundamentally different ways than robots working individually. Applications of Robot Swarms There are many applications for swarms of robots. In all these applications, individual robots must work independently, only communicating with other nearby robots. Software from Insects? The main goal of my research is to understand how to use local interactions between nearby robots to produce large-scale group behaviors from the entire swarm. However, developing swarm software from the "top down", i.e. by starting with the group application and trying to determine the individual behaviors that it arises from, is very difficult. The Future Primitive Behaviors orbitRobot (4,027 KB mpg)

Émergence Un article de Wikipédia, l'encyclopédie libre. L’émergence est un concept philosophique apparu au XIXe siècle grossièrement résumé par l'adage « le tout est plus que la somme de ses parties ». Plus précisément, une propriété peut être qualifiée d’émergente si elle « résulte » de propriétés plus fondamentales tout en demeurant « nouvelle » ou « irréductible » à celles-ci[1]. Ce concept propose ainsi de concilier dans les sciences une approche moniste avec une opposition au réductionnisme, c'est-à-dire postulant une unité fondamentale dans la composition de la nature (que ce soit la matière inerte, les organismes vivants ou le psychisme) mais déniant la possibilité d'une connaissance intégrale de ces phénomènes par la simple connaissance de leurs composants fondamentaux. L'enjeu des divers émergentismes proposés depuis lors étant précisément celui de la clarification des termes « résulter », « nouvelle » ou « irréductible », et de leurs différentes acceptions possibles.

Robotic cheetah 'breaks speed record for legged robots' 6 March 2012Last updated at 06:33 ET Footage of the robot in action - courtesy Darpa A headless robot dubbed "Cheetah" has set a new world speed record, according to its owners. The US Defense Advanced Research Projects Agency said the four-legged machine achieved 18mph (29km/h) on a laboratory treadmill. The agency said the previous land speed record by a legged robot was 13.1mph. Darpa said that the project was part of efforts to develop robots designed to "more effectively assist war fighters across a greater range of missions". Darpa - which is run by the Pentagon - funded the Massachusetts robotics company Boston Dynamics to build the machine. "We plan to get off the treadmill and into the field as soon as possible," said the firm's chief robotics scientist, Alfred Rizzi, in a statement. "We really want to understand what is possible for fast-moving robots." Animal designs The robot's movements have been modelled on those of fast-running animals in the wild.

Ant colony optimization algorithms Ant behavior was the inspiration for the metaheuristic optimization technique This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis,[1][2] the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. Overview[edit] Summary[edit] In the natural world, ants (initially) wander randomly, and upon finding food return to their colony while laying down pheromone trails. Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength. Common extensions[edit] Here are some of most popular variations of ACO Algorithms. to state where to

Airborne robot swarms are making complex moves (w/ video) (PhysOrg.com) -- The GRASP Lab at the University of Pennsylvania this week released a video that shows their new look in GRASP Lab robotic flying devices. They are now showing flying devices with more complex behavior than before, in a fleet of flying devices that move in packs, navigate spaces with obstacles, flip over and retain position, and carry out formation flying, The researchers have cut down these robotic creature-like drones to small size to what they call “nano-quadrotors.” The video shows them in action: not just engaged in formation flying, but also creating an impressive looking figure-eight pattern. The video says as much about the GRASP Lab as the flying machines, in that the GRASP Labs seems intent on raising the bar on what robot swarms can achieve. Still, the video is clear proof that the team developers, Alex Kushleyev, Daniel Mellinger, and Vijay Kumar, are able to showcase complex autonomous swarm behavior. The key word is agile. More information: www.swarms.org/

CS 223A : Introduction to Robotics Winter Quarter 2014 Announcements Schedule Homework Homework Guidelines: Homework is due by 12:50 pm on the due date. Systémique La systémique est une méthode d'étude ou façon de penser les objets complexes. Forgée sémantiquement à partir du mot en grec ancien systema, signifiant « ensemble organisé », elle privilégie une approche globale, holiste, la pluralité des perspectives selon différentes dimensions ou à différents niveaux d'organisation, et surtout la prise en compte des relations et interactions entre composants. Apparue progressivement au milieu du XXe siècle, la systémique s'est construite en opposition à la tradition analytique cartésienne et à d'autres formes de réductionnisme, qui tendent à découper le tout en parties indépendantes et montraient leurs limites dans la compréhension de la réalité. Éclairage[modifier | modifier le code] Les principes de la systémique ont la particularité de venir d'à peu près tous les domaines de la science et d'être également applicable à chacun d'eux. Historique[modifier | modifier le code] Les courants précurseurs[modifier | modifier le code]

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