Chao Yan

From Field to Planning: Learning Temporal Polar Gradient Fields for Vision-based AAV Trajectory Planning in Dynamic Environments

Autonomous Aerial Vehicle (AAV) trajectory planning requires real-time and accurate safety gradient guidance, especially in dynamic environments. Existing methods typically rely on static maps and dynamic obstacle tracking to construct gradient fields, imposing heavy computational burdens and yielding conservative traj...

Knowledge-Guided Multi-Agent Reinforcement Learning for Multi-AAV Cooperative Pursuit With Sparse Team Rewards