Revisiting the Minimum Constraint Removal Problem in Mobile Robotics
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Abstract (arXiv)
The minimum constraint removal problem seeks to find the minimum number of constraints, i.e., obstacles, that need to be removed to connect a start to a goal location with a collision-free path. This problem is NP-hard and has been studied in robotics, wireless sensing, and computational geometry. This work contributes to the existing literature by presenting and discussing two results. The first result shows that the minimum constraint removal is NP-hard for simply connected obstacles where each obstacle intersects a constant number of other obstacles. The second result demonstrates that for n simply connected obstacles in the plane, instances of the minimum constraint removal problem with minimum removable obstacles lower than (n+1)/3 can be solved in polynomial time. This result is also empirically validated using several instances of randomly sampled axis-parallel rectangles.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 May 2023.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networkscited by 2
- 2025Locally Optimal Solutions to Constraint Displacement Problems via Path-Obstacle Overlapscited by 1
- 2026A Horizon-slicing Approach to Minimum Obstacle Displacement Planning for Robot Navigationcited by 0
- 2026A Horizon-slicing Approach to Minimum Obstacle Displacement Planning for Robot Navigation19 Sep 2026
- 2025Locally Optimal Solutions to Constraint Displacement Problems via Path-Obstacle Overlaps15 Nov 2025
- 2025A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks10 Mar 2025