Multi-Robot Goal Conflict Resolution Under Communication Constraints Using Spatial Approximation And Strategic Caching

We consider the problem of distributed goal conflict resolution in multi-robot systems while remaining resilient to intermittent communication losses between robots. Our proposed approach uses a spatial approximation technique called alpha-shape to represent the regions that have been explored by robots followed by a O(log n) algorithm that incrementally combines and shares the alpha-shape information between robots along the robots' communication tree and rapidly checks for conflicts of a robot's selected location. We provide theoretical guarantees of the time complexity of our proposed algorithm along with experimental results with simulated and physical robots in different environments. The results show that our approach can rapidly determine conflicts between goal locations selected by multiple robots as well as reduce message loss and re-transmissions between robots. These result in more efficient inter-robot communications as well as less extraneous distance traveled by robots, as compared to a flooding-based communications approach. (C) 2020 Published by Elsevier B.V.