Distributed behavior collaboration for self-reconfigurable robots

This paper describes a distributed and decentralized approach for modules in a self-reconfigurable robot to select appropriate behaviors based on four factors: the current global task, the local topological location in the current configuration, the local state/sensor information, and the received messages from their neighbors. This approach does not assume any unique global identifiers for the modules, and is robust for reconfigurations of modules. The approach is enabled by the extended neighbor topology built upon a previous local topology representation and a hormone-inspired communication and control protocols. Experimental results on the CONRO robot have shown some unique features of this approach for the control of self-reconfigurable robots in general.