Pushing Through Clutter with Movability Awareness of Blocking Obstacles
Joris J. Weeda, Saray Bakker, Gang Chen, Javier Alonso-Mora
Abstract
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-amrISVG-MPPI
BibTeX
@inproceedings{icra2025_pushingthroughcl,
title = {Pushing Through Clutter with Movability Awareness of Blocking Obstacles},
author = {Joris J. Weeda and Saray Bakker and Gang Chen and Javier Alonso-Mora},
booktitle = {ICRA 2025},
year = {2025}
}