An Efficient Acyclic Contact Planner for Multiped Robots
- Submitting institution
-
University of Edinburgh
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 84702945
- Type
- D - Journal article
- DOI
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10.1109/TRO.2018.2819658
- Title of journal
- IEEE Transactions on Robotics
- Article number
- -
- First page
- 586
- Volume
- 34
- Issue
- 3
- ISSN
- 1552-3098
- Open access status
- Deposit exception
- Month of publication
- April
- 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
-
5
- Research group(s)
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D - Language, Interaction and Robotics
- Citation count
- 33
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Introduced two formal properties that break a combinatorial problem so far only addressed using brute force. Led to the design of a motion generation algorithm for legged robots, able to address in a matter of seconds scenarios where minutes to hours were required before. The performance gain proved pivotal and allowed for the generation of the first public legged motion database (hpp-loco dataset), which underpins the H2020 project Memmo. The associated Open Source software (humanoid path planner / rbprm) is used within (Geisert ‘19 TAROS) and outside the consortium in Japan (Kumagai ‘20 RAL) and Australia (Short ‘17 RAL).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -