6 papers
Probabilistic Energy Modeling Unifies Versatile Swarm Control
Xiang Zhou, Xiangyu Zhu, Xintong Wang +5
Robotic swarms must coordinate across diverse missions, yet existing controllers often require redesign, retuning, or retraining when objectives change. Here we show that probabili…
Distributed Stochastic Optimal Control for Pattern-Oriented Swarms
Qingrui Zhang, Chenghao Yu, Feng Xue +1
While offering significant promise for diverse applications, pattern-oriented swarms encounter multifaceted challenges in geometric control, self-organization, and safe navigation…
PILOT: Privileged Imitation Learning for End-to-End Motion Planning of Autonomous UAVs under Partial Observability
Qingrui Zhang, Feng Xue, Xiang Zhou +1
Autonomous navigation in cluttered environments is hampered by partial observability and dynamic constraints. This paper presents PILOT, a constraint-aware privileged imitation lea…
Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales
Yang Li, Feng Xue, Fan Mo +6
Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existing approaches often address the…
Learning Efficient Flocking Control based on Gibbs Random Fields
Dengyu Zhang, Chenghao, Feng Xue +1
Flocking control is essential for multi-robot systems in diverse applications, yet achieving efficient flocking in congested environments poses challenges regarding computation bur…
AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuit
Yang Li, Junfan Chen, Feng Xue +5
Adaptive teaming-the capability of agents to effectively collaborate with unfamiliar teammates without prior coordination-is widely explored in virtual video games but overlooked i…