Evaluating performance of multiple RRTs

Clifton, M; Paul, G; Kwok, N; Liu, D; Wang, DL

Evaluating performance of multiple RRTs

Clifton, M Paul, G

Kwok, N Liu, D

Wang, DL

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Publication Type:: Conference Proceeding
Citation:: 2008 IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, MESA 2008, 2008, pp. 564 - 569
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Clifton, M	en_US
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020	en_US
dc.contributor.author	Kwok, N	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.contributor.author	Wang, DL	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	2008 IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, MESA 2008, 2008, pp. 564 - 569	en_US
dc.identifier.isbn	9781424423682	en_US
dc.identifier.uri	http://hdl.handle.net/10453/12915
dc.description.abstract	This paper presents experimental results evaluating the performance of a new multiple Rapidly-exploring Random Tree (RRT) algorithm. RRTs are randomised planners especially adept at solving difficult, high-dimensional path planning problems. However, environments with low-connectivity due to the presence of obstacles can severely affect convergence. Multiple RRTs have been proposed as a means of addressing this issue, however, this approach can adversely affect computational efficiency. This paper introduces a new and simple method which takes advantage of the benefits of multiple trees, whilst ensuring the computational burden of maintaining them is minimised. Results indicate that multiple RRTs are able to reduce the logarithmic complexity of the search, most notably in environments with high obstacle densities. © 2008 IEEE.	en_US
dc.relation.ispartof	2008 IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, MESA 2008	en_US
dc.relation.isbasedon	10.1109/MESA.2008.4735749	en_US
dc.title	Evaluating performance of multiple RRTs	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0905 Civil Engineering	en_US
dc.location.activity	Beijing, China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

This paper presents experimental results evaluating the performance of a new multiple Rapidly-exploring Random Tree (RRT) algorithm. RRTs are randomised planners especially adept at solving difficult, high-dimensional path planning problems. However, environments with low-connectivity due to the presence of obstacles can severely affect convergence. Multiple RRTs have been proposed as a means of addressing this issue, however, this approach can adversely affect computational efficiency. This paper introduces a new and simple method which takes advantage of the benefits of multiple trees, whilst ensuring the computational burden of maintaining them is minimised. Results indicate that multiple RRTs are able to reduce the logarithmic complexity of the search, most notably in environments with high obstacle densities. © 2008 IEEE.

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http://hdl.handle.net/10453/12915