Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives

• URL: http://arxiv.org/abs/2507.01198v1
• Date: Tue, 01 Jul 2025 21:33:33 GMT
• Title: Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives
• Authors: Benjamin Kraljusic, Zlatan Ajanovic, Nermin Covic, Bakir Lacevic,
• Abstract summary: This work proposes a motion planning algorithm for robotic manipulators that combines sampling-based and search-based planning methods.<n>The core contribution of the proposed approach is the usage of burs of free configuration space (C-space) as adaptive motion primitives.<n>Results demonstrate that the bur-based approach outperforms fixed-primitive planning in complex scenarios.
• Score: 1.8874301050354767
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: This work proposes a motion planning algorithm for robotic manipulators that combines sampling-based and search-based planning methods. The core contribution of the proposed approach is the usage of burs of free configuration space (C-space) as adaptive motion primitives within the graph search algorithm. Due to their feature to adaptively expand in free C-space, burs enable more efficient exploration of the configuration space compared to fixed-sized motion primitives, significantly reducing the time to find a valid path and the number of required expansions. The algorithm is implemented within the existing SMPL (Search-Based Motion Planning Library) library and evaluated through a series of different scenarios involving manipulators with varying number of degrees-of-freedom (DoF) and environment complexity. Results demonstrate that the bur-based approach outperforms fixed-primitive planning in complex scenarios, particularly for high DoF manipulators, while achieving comparable performance in simpler scenarios.

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