Collision-free navigation in cluttered environments with static and dynamic obstacles is
essential for many multi-robot tasks. Dynamic obstacles may also be interactive, ie, their …

Recent advancements in autonomous mobile robots (AMRs), such as aerial drones, ground
vehicles, and quadrupedal robots, have significantly impacted the fields of infrastructure …

Communication delays can be catastrophic for multiagent systems. However, most existing
state-of-the-art multiagent trajectory planners assume perfect communication and therefore …

End-to-end deep reinforcement learning (DRL) for quadrotor control promises many benefits–
easy deployment, task generalization and real-time execution capability. Prior end-to-end …

Multi-robot collision-free and deadlock-free navigation in cluttered environments with static
and dynamic obstacles is a fundamental problem for many applications. We introduce …

Future warfare will require Command and Control (C2) personnel to make decisions at
shrinking timescales in complex and potentially ill-defined situations. Given the need for …

There are many industrial, commercial and social applications for multi-agent planning for
multirotors such as autonomous agriculture, infrastructure inspection and search and …

To plan the trajectories of a large and heterogeneous swarm, sequential or synchronous
distributed methods usually become intractable, due to the lack of global connectivity and …

Formation flight holds significant potential for various applications involving aerial robot
swarms. However, current methodologies lack the capability to autonomously execute large …

This paper presents a distributed rule-based Lloyd algorithm (RBL) for multi-robot motion
planning and control. The main limitations of the basic Loyd-based algorithm (LB) concern …