6 papers
Co-jump: Cooperative Jumping with Quadrupedal Robots via Multi-Agent Reinforcement Learning
Shihao Dong, Yeke Chen, Zeren Luo +8
While single-agent legged locomotion has witnessed remarkable progress, individual robots remain fundamentally constrained by physical actuation limits. To transcend these boundari…
Learning Human-Like Badminton Skills for Humanoid Robots
Yeke Chen, Shihao Dong, Xiaoyu Ji +10
Realizing versatile and human-like performance in high-demand sports like badminton remains a formidable challenge for humanoid robotics. Unlike standard locomotion or static manip…
Flow-Aided Flight Through Dynamic Clutters From Point To Motion
Bowen Xu, Zexuan Yan, Minghao Lu +7
Challenges in traversing dynamic clutters lie mainly in the efficient perception of the environmental dynamics and the generation of evasive behaviors considering obstacle movement…
Breaking the Static Assumption: A Dynamic-Aware LIO Framework Via Spatio-Temporal Normal Analysis
Chen Zhiqiang, Le Gentil Cedric, Lin Fuling +5
This paper addresses the challenge of Lidar-Inertial Odometry (LIO) in dynamic environments, where conventional methods often fail due to their static-world assumptions. Traditiona…
HEPP: Hyper-efficient Perception and Planning for High-speed Obstacle Avoidance of UAVs
Minghao Lu, Xiyu Fan, Bowen Xu +5
High-speed obstacle avoidance of uncrewed aerial vehicles (UAVs) in cluttered environments is a significant challenge. Existing UAV planning and obstacle avoidance systems can only…
Flying in Highly Dynamic Environments with End-to-end Learning Approach
Xiyu Fan, Minghao Lu, Bowen Xu +1
Obstacle avoidance for unmanned aerial vehicles like quadrotors is a popular research topic. Most existing research focuses only on static environments, and obstacle avoidance in e…