Contingency Model-based Control (CMC) for communicationless cooperative collision avoidance in robot swarms

Cooperative collision avoidance between autonomous robots, or ‘agents,’ in swarm operations remains an open challenge. Assuming a decentralized architecture, each agent is responsible for making its own decisions and implementing them by choosing control actions. For avoiding collisions, most existing approaches rely on a (wireless) communication network between (some of) the agents. In reality, however, communication is brittle. It may be affected by latencies, irregular delays, packet losses, and faulty data transmissions. Moreover, it is subject to adversarial attacks, such as jamming or spoofing. This paper proposes Contingency Model-based Control (CMC) as a decentralized cooperative approach that does not rely on communication. Instead, it requires only (exact) measurements of the current state of other agents, using onboard sensors. The CMC algorithm is based on consensual rules that are designed offline for all agents, similar to traffic rules. This includes the definition of a contingency trajectory for each robot and perpendicular bisecting planes as collision avoidance constraints. The setup permits a full guarantee of recursive feasibility and collision avoidance between all members of the swarm in closed-loop operation. CMC naturally satisfies the plug & play paradigm, i.e., new robots may enter (or leave) the swarm dynamically. The effectiveness of the CMC regime is demonstrated in two numerical examples, showing that the collision avoidance guarantee is intact and the robot swarm operates smoothly in a constrained environment.