AffordTrajDP: Dynamic Affordance-Guided Visuomotor Policy Learning for Robotic Manipulation
技术动态
来源：arXiv cs.RO发布时间待核实
arXiv:2608.01603v2 Announce Type: replace Abstract: Affordance-guided imitation learning has shown impressive performance in robotic manipulation tasks by compressing visual perception into task-specific geometric constraints (e.g., fixed contact points). However, the commonly used static affordances can become inconsistent in precision-critical tasks or under object location perturbations, leading to post-contact trajectory drift.