Resilience Algorithm applied to trajectory tracking of a heterogeneous group of robots

In a multi-agent system, the presence of agents that intentionally share misleading information or have suffered a failure (non-cooperative agents) affects its normal operation. Specific characteristics of the connectivity graph of the system can help to avoid this situation. Here, a resilience algorithm for multi-agent systems is studied and applied so that the system is able to reach its global task. Specifically, the conditions on the connectivity graph, update rule and bounds on the deviation of shared information among the agents are studied so that a resilient consensus is achieved. Both, the algorithm and the analysis is applied in a group of heterogeneous robots whose global task is formation and trajectory tracking. Further, after the identification of non-cooperative agents, the re-configuration of the agents is such that the robustness of the graph is kept.