障害物の可動性を考慮した散らかった環境の押し退けナビゲーション
Pushing Through Clutter With Movability Awareness of Blocking Obstacles
障害物の可動性を連続値として扱い、Semantic Visibility GraphとMPPIを組み合わせて、接触力を抑えつつ障害物を押し退けて目的地へ到達する計画手法を提案した論文。
著者: Joris J. Weeda, Saray Bakker, Gang Chen, Javier Alonso-Mora
分類: cs.RO
原文アブストラクト
Navigation Among Movable Obstacles (NAMO) poses a challenge for traditional path-planning methods when obstacles block the path, requiring push actions to reach the goal. We propose a framework that enables movability-aware planning to overcome this challenge without relying on explicit obstacle placement. Our framework integrates a global Semantic Visibility Graph and a local Model Predictive Path Integral (SVG-MPPI) approach to efficiently sample rollouts, taking into account the continuous range of obstacle movability. A physics engine is adopted to simulate the interaction result of the rollouts with the environment, and generate trajectories that minimize contact force. In qualitative and quantitative experiments, SVG-MPPI outperforms the existing paradigm that uses only binary movability for planning, achieving higher success rates with reduced cumulative contact forces. Our code is available at: https://github.com/tud-amr/SVG-MPPI
