Journal article
Informed sampling for asymptotically optimal path planning
- Abstract:
-
Anytime almost-surely asymptotically optimal planners, such as RRT∗, incrementally find paths to every state in the search domain. This is inefficient once an initial solution is found, as then only states that can provide a better solution need to be considered. Exact knowledge of these states requires solving the problem but can be approximated with heuristics. This paper formally defines these sets of states and demonstrates how they can be used to analyze arbitrary planning problems. It u...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
Bibliographic Details
- Publisher:
- IEEE Publisher's website
- Journal:
- IEEE Transactions on Robotics Journal website
- Volume:
- 34
- Issue:
- 4
- Pages:
- 966-984
- Publication date:
- 2018-06-22
- Acceptance date:
- 2018-02-19
- DOI:
- EISSN:
-
1941-0468
- ISSN:
-
1552-3098
Item Description
- Keywords:
- Pubs id:
-
pubs:865140
- UUID:
-
uuid:3e05d57b-4cff-46d2-9787-d3fdb5de4166
- Local pid:
- pubs:865140
- Source identifiers:
-
865140
- Deposit date:
- 2019-05-09
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2018
- Notes:
- © 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/tro.2018.2830331.
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record