In this work we consider a swarm of agents, which are shaped as bars with a certain orientation in the state space. Members of the swarm have to reach an aggregate state, while guaranteeing the collision avoidance and possibly achieving an angular consensus.

In this work we address the problem of dynamically tuning gains for multi-agent networks under potential- based control design. We propose a distributed and adaptive gain controller that preserves a designed pairwise interaction strength, independent of the network size.

In this work, we propose a general coordinated motion framework for multi-robot systems with triangular FOVs capable of guaranteeing stability under asymmetric (directed) interactions. By proving that asymmetry in multi-robot interactions can lead to degenerate configurations for which a fully decentralized controller may be insufficient to achieve coordination, we introduce a switching control mechanism that achieves adaptive decentralization, enabling collaborative behaviors that seek support of a centralized planner for situations that are inherently unstable.

In this work we consider the problem of coordinating a multi-agent system equipped with limited field of view sensors. We propose a generic coordination control framework for directed interactions and provide one of its application to maintain connectivity while optimizing the quality of the field of views.

In this work we study the problem of designing a local interaction protocol that drives a set of agents towards a region delimited by the positions of another set of agents, under the presence of adversaries in the network, i.e., agents that intentionally or accidentally try to disrupt the objective of the multi-agent system.