Accurate self and relative state estimation are the critical preconditions for completing swarm
tasks, eg, collaborative autonomous exploration, target tracking, search and rescue. This …

Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system
that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot …

Although the use of multiple unmanned aerial vehicles (UAVs) has great potential for fast
autonomous exploration, it has received far too little attention. In this article, we present a …

Mutual localization provides a consensus of reference frame as an essential basis for
cooperation in multi-robot systems. Previous works have developed certifiable and robust …

Recent research has demonstrated the potential of reinforcement learning (RL) in enabling
effective multi-robot collaboration, particularly in social dilemmas where robots face a trade …

Mutual localization is essential for coordination and cooperation in multi-robot systems.
Previous works have tackled this problem by assuming available correspondences between …

Perception is necessary for autonomous navigation in an unknown area crowded with
obstacles. It's challenging for a robot to navigate safely without any sensors that can sense …

Autonomous exploration of unknown environments with multiple Unmanned Aerial Vehicles
(UAVs) is a challenging problem. In this article, we present DPPM, a Decentralized …

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

Fully decentralized, multiagent trajectory planners enable complex tasks like search and
rescue or package delivery by ensuring safe navigation in unknown environments …