KABouM: Knowledge-Level Action and Bounding Geometry Motion Planner
- Submitting institution
-
Heriot-Watt University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 16610194
- Type
- D - Journal article
- DOI
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10.1613/jair.5560
- Title of journal
- Journal of Artificial Intelligence Research
- Article number
- -
- First page
- 323
- Volume
- 61
- Issue
- -
- ISSN
- 1076-9757
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a new method for combining high-level plan-based reasoning with low-level motion planning, for use with robot systems. This is the first approach to use a state-of-the-art epistemic planner which is able to model many types of uncertainty that arise in real-world domains and generate plans with contingencies. A rigorous evaluation on real robot systems is performed. This work developed from the EU-funded JAMES project (Grant no. 270435) and involved collaboration with top robotics groups from Stanford University and the Technical University of Munich. This paper was published in one of the top artificial intelligence journals.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
