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Cited by 167

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Quasi-randomized path planning

Branicky, M.S., LaValle, S.M., Olson, K., Libo Yang·2002·Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)

Abstract

We propose the use of quasi-random sampling techniques for path planning in high-dimensional configuration spaces. Following similar trends from related numerical computation fields, we show several advantages offered by these techniques in comparison to random sampling. Our ideas are evaluated in the context of the probabilistic roadmap (PRM) framework. Two quasi-random variants of PRM- based planners are proposed: 1) a classical PRM with quasi-random sampling; and 2) a quasi-random lazy-PRM. Both have been implemented, and are shown through experiments to offer some performance advantages in comparison to their randomized counterparts.

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Metadata

Authors
Branicky, M. S., LaValle, S. M., Olson, K., & Yang, L.
Venue
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)
Publisher
IEEE
Published
2002-11-13
Volume
2
Pages
1481-1487
ISSN
1050-4729 (ISSN-L)
OpenAlex
W2104171123
Cited by
167
References
2
FWCI
8.85
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Quasi-randomized path planning. https://app.cochat.ai/papers/10.1109/robot.2001.932820
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Branicky, M. S., LaValle, S. M., Olson, K., & Yang, L. (2002). Quasi-randomized path planning. Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164). https://doi.org/10.1109/robot.2001.932820

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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.