Robomotion: Scalable, Physically Stable Locomotion for Self-reconfigurable Robots

Abstract

Self-reconfigurable robots have an intriguingly flexible design, composing a single robot with many small modules that can autonomously move to transform the robot’s shape and structure. Scaling to a large number of modules is necessary to achieve great flexibility, so each module may only have limited processing and memory resources. This paper introduces a novel distributed locomotion algorithm for lattice-style self-reconfigurable robots which uses constant memory per module with constant computation and communication for each attempted module movement. Our algorithm also guarantees physical stability in the presence of gravity. By utilizing some robot modules to create a static support structure, other modules are able to move freely through the interior of this structure with minimal path planning and without fear of causing instabilities or losing connectivity. This approach also permits the robot’s locomotion speed to remain nearly constant even as the number of modules in the robot grows very large. Additionally,we have developed methods to overcome dropped messages between modules or delays in module computation or movement. Empirical results from our simulation are also presented to demonstrate the scalability and locomotion speed advantages of this approach.