mlsanityData to 14 Oct 2026

A Horizon-slicing Approach to Minimum Obstacle Displacement Planning for Robot Navigation

arXiv 2609.22974 ↗First posted 19 Sep 2026cs.RO cs.AIcited by 0

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Abstract (arXiv)

In this paper, we investigate the Minimum Obstacle Displacement Planning problem from a robot motion planning perspective. The problem involves determining a feasible path to a goal location by displacing movable obstacles when no collision-free path initially exists. We show that this problem is computationally challenging and, in particular, NP-hard when obstacles are modeled as polygons in the plane. Besides an exact formulation of the minimum obstacle displacement problem generalizing other problems in the literature, and the associated optimal solution, this paper proposes an approximate solution that is less intensive from a computational standpoint, and differs from the optimal solution by a fraction of the optimal cost, being able to trade-off between path length and amount of obstacle displacements.

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References · 14

  1. 2016FFRob: Leveraging Symbolic Planning for Efficient Task and Motion Planningcited by 34
  2. 2018Detection, localisation and tracking of pallets using machine learning techniques and 2D range datacited by 10
  3. 2013Incremental Sampling-based Algorithm for Minimum-violation Motion Planningcited by 9
  4. 2018On the manipulation of articulated objects in human-robot cooperation scenarioscited by 7
  5. 2021MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Spacecited by 7
  6. 2021Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspacescited by 7
  7. 2022Minimum Displacement Motion Planning for Movable Obstaclescited by 4
  8. 2025NAMO-LLM: Efficient Navigation Among Movable Obstacles with Large Language Model Guidancecited by 4
  9. 2023Revisiting the Minimum Constraint Removal Problem in Mobile Roboticscited by 3
  10. 2023Safe motion planning with environment uncertaintycited by 3
  11. 2025A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networkscited by 2
  12. 2025Pushing Through Clutter With Movability Awareness of Blocking Obstaclescited by 1
2 more
  1. 2025Efficient Navigation Among Movable Obstacles using a Mobile Manipulator via Hierarchical Policy Learningcited by 1
  2. 2025Locally Optimal Solutions to Constraint Displacement Problems via Path-Obstacle Overlapscited by 1

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