Constant Bearing Pursuit on Branching Graphs
This work addresses the reliability of autonomous robot systems by providing a more flexible pursuit framework, though it appears incremental as it builds on existing constant bearing pursuit methods.
The paper tackles the problem of generalizing cyclic pursuit frameworks for autonomous robot collectives by introducing a modified version that allows any weakly connected pursuit graph with outdegree 1, leading to improved system reliability by enabling agents to join or leave without perturbing others.
Cyclic pursuit frameworks provide an efficient way to create useful global behaviors out of pairwise interactions in a collective of autonomous robots. Earlier work studied cyclic pursuit with a constant bearing (CB) pursuit law, and has demonstrated the existence of a variety of interesting behaviors for the corresponding dynamics. In this work, by attaching multiple branches to a single cycle, we introduce a modified version of this framework which allows us to consider any weakly connected pursuit graph where each node has an outdegree of 1. This provides a further generalization of the cyclic pursuit setting. Then, after showing existence of relative equilibria (rectilinear or circling motion), pure shape equilibria (spiraling motion) and periodic orbits, we also derive necessary conditions for stability of a 3-agent collective. By paving a way for individual agents to join or leave a collective without perturbing the motion of others, our approach leads to improved reliability of the overall system.