Advanced BIT* (ABIT*): Sampling-based planning with advanced graph-search techniques
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- Publication Date
- Abstract
Path planning is an active area of research essential for many applications in robotics. Popular techniques include graph-based searches and sampling-based planners. These approaches are powerful but have limitations.
This paper continues work to combine their strengths and mitigate their limitations using a unified planning paradigm. It does this by viewing the path planning problem as the two subproblems of search and approximation and using advanced graph-search techniques on a sampling-based approximation.
This perspective leads to Advanced BIT*. ABIT* combines truncated anytime graph-based searches, such as ATD*, with anytime almost-surely asymptotically optimal sampling-based planners, such as RRT*. This allows it to quickly find initial solutions and then converge towards the optimum in an anytime manner. ABIT* outperforms existing single-query, sampling-based planners on the tested problems in R4 and R8, and was demonstrated on real-world problems with NASA/JPL-Caltech.
- Video
- Presentation
- Publication Details
- Type
- Full-Paper-Refereed Conference Paper
- Conference
- IEEE International Conference on Robotics and Automation (ICRA)
- Pages
- 130–136
- Digital Object Identifier
- 10.1109/ICRA40945.2020.9196580
- arXiv Identifier
- 2002.06589 [cs.RO]
- Manuscript
- Open-Access PDF
- https://arxiv.org/pdf/2002.06589
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- Google Scholar
- BibTeX Entry
@inproceedings{strub_icra20a,
author = {Marlin P Strub and Jonathan D Gammell},
title = {Advanced {BIT*} ({ABIT*}): Sampling-based planning with advanced graph-search techniques},
booktitle = {Proceedings of the {IEEE} International Conference on Robotics and Automation ({ICRA})},
year = {2020},
pages = {130--136},
month = {31 } # may #{ -- 31 } # aug,
doi = {10.1109/ICRA40945.2020.9196580},
}