A Real-Time local path planning method based on SVM for UGV

Zhuge, C; Tang, Z

A Real-Time local path planning method based on SVM for UGV

Zhuge, C Tang, Z

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Publication Type:: Journal Article
Citation:: Boletin Tecnico/Technical Bulletin, 2017, 55 (17), pp. 487 - 499
Issue Date:: 2017-11-01

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Field	Value	Language
dc.contributor.author	Zhuge, C	en_US
dc.contributor.author	Tang, Z	en_US
dc.date.issued	2017-11-01	en_US
dc.identifier.citation	Boletin Tecnico/Technical Bulletin, 2017, 55 (17), pp. 487 - 499	en_US
dc.identifier.issn	0376-723X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126855
dc.description.abstract	Path planning is one of essentials of unmanned ground vehicle (UGV). For the case of poor lighting and weather, traditional vision based methods can not extract effective route boundaries to generate reasonable path stably in unstructured road. By ta king advantage of distance-sensing technology (e.g. 64-beam LiDAR), th is paper proposes an efficient real-time path planning approach. In this approach, given grid map fro m 64-bea m LiDAR, obstacles on both sides of the road are regarded as two classes fed to Support Vector Machine (SVM) to generate an initial safe path. During driving, a time weight based least square fitting is adopted to refine path fro m mu ltiple safe paths which will be described by quartic polynomial, providing stable driving route. Co mbined with UGV's state, controls points from the refined path are adopted to generate the final path through Bezier curve fitting. Experiments on real UGV under different road scenario are conducted, showing that the proposed method can obtain stable and reasonable path with promising performance.	en_US
dc.relation.ispartof	Boletin Tecnico/Technical Bulletin	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A Real-Time local path planning method based on SVM for UGV	en_US
dc.type	Journal Article
utslib.citation.volume	17	en_US
utslib.citation.volume	55	en_US
utslib.for	0906 Electrical and Electronic Engineering	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 Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.issue	17	en_US
pubs.publication-status	Published	en_US
pubs.volume	55	en_US

Abstract:

Path planning is one of essentials of unmanned ground vehicle (UGV). For the case of poor lighting and weather, traditional vision based methods can not extract effective route boundaries to generate reasonable path stably in unstructured road. By ta king advantage of distance-sensing technology (e.g. 64-beam LiDAR), th is paper proposes an efficient real-time path planning approach. In this approach, given grid map fro m 64-bea m LiDAR, obstacles on both sides of the road are regarded as two classes fed to Support Vector Machine (SVM) to generate an initial safe path. During driving, a time weight based least square fitting is adopted to refine path fro m mu ltiple safe paths which will be described by quartic polynomial, providing stable driving route. Co mbined with UGV's state, controls points from the refined path are adopted to generate the final path through Bezier curve fitting. Experiments on real UGV under different road scenario are conducted, showing that the proposed method can obtain stable and reasonable path with promising performance.

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http://hdl.handle.net/10453/126855