断熱材を用いた熱拡散に着想を得た衝突回避動作計画
Denoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planning
単一の視覚入力から、到達可能な目標の生成と障害物回避を同時に行う拡散モデルベースの動作計画手法を提案し、衝突回避カーネルにより堅牢性を実証した。
著者: Junwoo Chang, Hyunwoo Ryu, Jiwoo Kim, Soochul Yoo, Jongeun Choi, Joohwan Seo, Nikhil Prakash, Roberto Horowitz
分類: cs.RO, cs.AI, cs.LG
原文アブストラクト
Diffusion models have risen as a powerful tool in robotics due to their flexibility and multi-modality. While some of these methods effectively address complex problems, they often depend heavily on inference-time obstacle detection and require additional equipment. Addressing these challenges, we present a method that, during inference time, simultaneously generates only reachable goals and plans motions that avoid obstacles, all from a single visual input. Central to our approach is the novel use of a collision-avoiding diffusion kernel for training. Through evaluations against behavior-cloning and classical diffusion models, our framework has proven its robustness. It is particularly effective in multi-modal environments, navigating toward goals and avoiding unreachable ones blocked by obstacles, while ensuring collision avoidance. Project Website: https://sites.google.com/view/denoising-heat-inspired
