Communications of the ACM - Robots: intelligence, versatility, adaptivity
Biologically Inspired Robots: Serpentile Locomotors and Manipulators
Biologically Inspired Robots: Serpentile Locomotors and Manipulators
Decentralized synchronization protocols with nearest neighbor communication
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Multimode locomotion via SuperBot reconfigurable robots
Autonomous Robots
Sensing-based shape formation on modular multi-robot systems: a theoretical study
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Engineering self-adaptive modular robotics: a bio-inspired approach
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Collective decision-making in multi-agent systems by implicit leadership
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 3 - Volume 3
Laplacian-based consensus on spatial computers
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Macro Programming a Spatial Computer with Bayesian Networks
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
A Self-adaptive Framework for Modular Robots in a Dynamic Environment: Theory and Applications
International Journal of Robotics Research
Cellular automata models for cooperation in multirobot systems
IMMURO'12 Proceedings of the 11th WSEAS international conference on Instrumentation, Measurement, Circuits and Systems, and Proceedings of the 12th WSEAS international conference on Robotics, Control and Manufacturing Technology, and Proceedings of the 12th WSEAS international conference on Multimedia Systems & Signal Processing
Self-adaptation for mobile robot algorithms using organic computing principles
ARCS'13 Proceedings of the 26th international conference on Architecture of Computing Systems
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Biological systems achieve amazing adaptive behavior with local agents performing simple sensing and actions. Modular robots with similar properties can potentially achieve self-adaptation tasks robustly. Inspired by this principle, we present a generalized distributed consensus framework for self-adaptation tasks in modular robotics. We demonstrate that a variety of modular robotic systems and tasks can be formulated within such a framework, including (1) an adaptive column that can adapt to external force, (2) a modular gripper that can manipulate fragile objects, and (3) a modular tetrahedral robot that can locomote towards a light source. We also show that control algorithms derived from this framework are provably correct. In real robot experiments, we demonstrate that such a control scheme is robust towards real world sensing and actuation noise. This framework can potentially be applied to a wide range of distributed robotics applications.