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- Publisher Website: 10.1109/FPT.2013.6718355
- Scopus: eid_2-s2.0-84894224565
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Conference Paper: Acceleration of real-time Proximity Query for dynamic active constraints
Title | Acceleration of real-time Proximity Query for dynamic active constraints |
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Authors | |
Issue Date | 2013 |
Citation | FPT 2013 - Proceedings of the 2013 International Conference on Field Programmable Technology, 2013, p. 206-213 How to Cite? |
Abstract | Proximity Query (PQ) is a process to calculate the relative placement of objects. It is a critical task for many applications such as robot motion planning, but it is often too computationally demanding for real-time applications, particularly those involving human-robot collaborative control. This paper derives a PQ formulation which can support non-convex objects represented by meshes or cloud points. We optimise the proposed PQ for reconfigurable hardware by function transformation and reduced precision, resulting in a novel data structure and memory architecture for data streaming while maintaining the accuracy of results. Run-time reconfiguration is adopted for dynamic precision optimisation. Experimental results show that our optimised PQ implementation on a reconfigurable platform with four FPGAs is 58 times faster than an optimised CPU implementation with 12 cores, 9 times faster than a GPU, and 3 times faster than a double precision implementation with four FPGAs. © 2013 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/199940 |
DC Field | Value | Language |
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dc.contributor.author | Chau, Thomas | - |
dc.contributor.author | Kwok, Kawai | - |
dc.contributor.author | Chow, Gary Chun Tak | - |
dc.contributor.author | Tsoi, Kuen Hung | - |
dc.contributor.author | Lee, Kithang | - |
dc.contributor.author | Tse, Zion | - |
dc.contributor.author | Cheung, Peter | - |
dc.contributor.author | Luk, Wayne | - |
dc.date.accessioned | 2014-07-26T23:10:56Z | - |
dc.date.available | 2014-07-26T23:10:56Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | FPT 2013 - Proceedings of the 2013 International Conference on Field Programmable Technology, 2013, p. 206-213 | - |
dc.identifier.uri | http://hdl.handle.net/10722/199940 | - |
dc.description.abstract | Proximity Query (PQ) is a process to calculate the relative placement of objects. It is a critical task for many applications such as robot motion planning, but it is often too computationally demanding for real-time applications, particularly those involving human-robot collaborative control. This paper derives a PQ formulation which can support non-convex objects represented by meshes or cloud points. We optimise the proposed PQ for reconfigurable hardware by function transformation and reduced precision, resulting in a novel data structure and memory architecture for data streaming while maintaining the accuracy of results. Run-time reconfiguration is adopted for dynamic precision optimisation. Experimental results show that our optimised PQ implementation on a reconfigurable platform with four FPGAs is 58 times faster than an optimised CPU implementation with 12 cores, 9 times faster than a GPU, and 3 times faster than a double precision implementation with four FPGAs. © 2013 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | FPT 2013 - Proceedings of the 2013 International Conference on Field Programmable Technology | - |
dc.title | Acceleration of real-time Proximity Query for dynamic active constraints | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/FPT.2013.6718355 | - |
dc.identifier.scopus | eid_2-s2.0-84894224565 | - |
dc.identifier.spage | 206 | - |
dc.identifier.epage | 213 | - |