2026
AVO-QP: Task-Adaptive Real-Time Obstacle Avoidance for Redundant Manipulators on Edge Platforms
RA-L 2026
We address real-time obstacle avoidance for redundant manipulators where tracking and safety constraints can conflict and render quadratic programs (QPs) infeasible. We propose AVO-QP, a sensor-guided velocity-level planner that fuses RGB-D depth with learned detection to maintain situational awaren