The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
A randomized roadmap method for path and manipulation planning
Abstract
This paper presents a new randomized roadmap method for motion planning for many DOF robots that can be used to obtain high quality roadmaps even when C-space is crowded. The main novelty in the authors' approach is that roadmap candidate points are chosen on C-obstacle surfaces. As a consequence, the roadmap is likely to contain difficult paths, such as those traversing long, narrow passages in C-space. The approach can be used for both collision-free path planning and for manipulation planning of contact tasks. Experimental results with a planar articulated 6 DOF robot show that, after preprocessing, difficult path planning operations can often be carried out in less than a second.
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Citations
Cites
Latombe, J.-C. (1991) · Springer eBooks · doi:10.1007/978-1-4615-4022-9 · Cited by 6,396
Robot Motion Planning: A Distributed Representation Approach
Barraquand, J., & Latombe, J.-C. (1991) · The International Journal of Robotics Research · doi:10.1177/027836499101000604 · Cited by 995
Numerical potential field techniques for robot path planning
Barraquand, J., Langlois, B., & Latombe, J.-C. (1992) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/21.148426 · Cited by 889
Gross motion planning—a survey
Hwang, Y. K., & Ahuja, N. (1992) · ACM Computing Surveys · doi:10.1145/136035.136037 · Cited by 826
Randomized preprocessing of configuration for fast path planning
Kavraki, L., & Latombe, J.-C. (2002) · Proceedings of the 1994 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.1994.350966 · Cited by 412
A search algorithm for motion planning with six degrees of freedom
Donald, B. R. (1987) · Artificial Intelligence · doi:10.1016/0004-3702(87)90069-5 · Cited by 216
A probabilistic learning approach to motion planning
Overmars, M. H., & Švestka, P. (1995) · Cited by 170
Assembly maintainability study with motion planning
Chang, H. T., & Li, T. (2002) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1995.525415 · Cited by 130
Parallel search algorithms for robot motion planning
Challou, D., Gini, M. L., & Kumar, V. (2002) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1993.292122 · Cited by 66
A practical approach to motion-planning for manipulators with many degrees of freedom
Faverjon, B., & Tournassoud, P. (1991) · OpenGrey (Institut de l'Information Scientifique et Technique) · Cited by 36
Cited by
RRT-connect: An efficient approach to single-query path planning
Kuffner, J. J., & LaValle, S. M. (2000) · Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065) · doi:10.1109/robot.2000.844730 · Cited by 3,555
Randomized Kinodynamic Planning
LaValle, S. M., & Kuffner, J. J. (2001) · The International Journal of Robotics Research · doi:10.1177/02783640122067453 · Cited by 3,254
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
Nasiriany, S., Liu, H., & Zhu, Y. (2022) · 2022 International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra46639.2022.9812140 · Cited by 91
Metadata
- Authors
- Amato, N. M., & Wu, Y.
- Venue
- Proceedings of IEEE International Conference on Robotics and Automation
- Publisher
- IEEE
- Published
- 2002-12-23
- Volume
- 1
- Pages
- 113-120
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2151402824
- Cited by
- 369
- References
- 10
- FWCI
- 16.29
- Type
- conference paper
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
