Pushing Through Clutter with Movability Awareness of Blocking Obstacles
Joris J. Weeda (Student TU Delft)
Saray Bakker (TU Delft - Mechanical Engineering)
G. Chen (TU Delft - Mechanical Engineering)
Javier Alonso-Mora (TU Delft - Mechanical Engineering)
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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.