Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911033369559040 |
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| author | Kraljusic, Benjamin Ajanovic, Zlatan Covic, Nermin Lacevic, Bakir |
| author_facet | Kraljusic, Benjamin Ajanovic, Zlatan Covic, Nermin Lacevic, Bakir |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01198 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives Kraljusic, Benjamin Ajanovic, Zlatan Covic, Nermin Lacevic, Bakir Robotics Artificial Intelligence Computational Geometry 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. |
| title | Search-Based Robot Motion Planning With Distance-Based Adaptive Motion Primitives |
| topic | Robotics Artificial Intelligence Computational Geometry |
| url | https://arxiv.org/abs/2507.01198 |