Abstract
Self-reconfigurable robots are built from modules which are autonomously able to change the way they are connected, thus changing the overall shape of the robot. This process is difficult to control because it involves the distributed coordination of large numbers of identical modules connected in time-varying ways.
We present an approach to self-reconfiguration where the desired configuration is grown from an initial seed module. Seeds produce growth by creating a recruitment gradient, using local communication, which spare modules climb to locate the seed. The growth is guided by a novel representation of the desired configuration, which is automatically generated from a 3D CAD model. This approach has two salient features: (1) the representation is concise, with a size proportional to the global shape rather than the number of modules and (2) there is a clean separation between the goal and the local, goal independent rules used by the modules. We demonstrate three implementations of the local rules for recruitment, and show how one can trade-off the number of moves and messages, against time taken to reconfigure.
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The Maersk Mc-Kinney Moller Institute for Production Technology, University of Southern Denmark, Denmark
K. Stoy
Division of Engineering and Applied Sciences, Harvard University, USA
R. Nagpal
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LAAS CNRS, 7 Avenue du Colonel Roche, 31077, Toulouse Cedex 4, France
Rachid Alami Ph.D. (Senior Scientist) & Raja Chatila Ph.D. (Senior Scientist) (Senior Scientist) & (Senior Scientist)
Research into Artifacts, Center for Engineering, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan
Hajime Asama Ph.D. (Professor) (Professor)
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Stoy, K., Nagpal, R. (2007). Self-Reconfiguration Using Directed Growth. In: Alami, R., Chatila, R., Asama, H. (eds) Distributed Autonomous Robotic Systems 6. Springer, Tokyo. https://doi.org/10.1007/978-4-431-35873-2_1
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