Automatic generating controller expressions and locomotion for UBot modular self-reconfigurable robot

Abstract

Chain-type self-reconfigurable robot (SRR), as a category of modular robots, is more suitable to implement whole body locomotion task, e.g. snake-like configuration squeezing through a narrow hole, legged-robot crossing over a rugged terrain. As SRR could construct diverse configurations and they are mostly super-redundant, it is challenging to plan these configurations' controller, especially for non-typical configurations. To resolve this problem, evolutionary computing paradigm is frequently used. However, the controller structure or expressions should be designed before evolving the parameters. Some researchers use fully connected CPG network as the default controller, but the parameter space is too large. Few scholars try to automatic generate reduced controller by topology and symmetry analysis, but their method is only applicable for limb-type configurations. In this paper, we propose a framework for automatic generating both controller expressions and locomotion, which combines topology analysis, functional substructure mapping, and isomorphic substructures constraints. This method can fit a large amount of configurations with different type of substructures. Taking UBot SRR as the instance, we realize and integrate the framework to the self-develop UBotSim software. The effectiveness is validated by extensive simulations/off-line optimizations of typical and non-typical configurations.