CuTE: Curb Tracking and Estimation

Kodagoda, KRS; Wijesoma, WS; Balasuriya, AP

CuTE: Curb Tracking and Estimation

Kodagoda, KRS

Wijesoma, WS Balasuriya, AP

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Control Systems Technology, 2006, 14 (5), pp. 951 - 957
Issue Date:: 2006-09-01

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Field	Value	Language
dc.contributor.author	Kodagoda, KRS https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Wijesoma, WS	en_US
dc.contributor.author	Balasuriya, AP	en_US
dc.date.issued	2006-09-01	en_US
dc.identifier.citation	IEEE Transactions on Control Systems Technology, 2006, 14 (5), pp. 951 - 957	en_US
dc.identifier.issn	1063-6536	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5840
dc.description.abstract	The number of road accident related fatalities and damages are reduced substantially by improving road infrastructure and enacting and imposing laws. Further reduction is possible through embedding intelligence onto the vehicles for safe decision making. Road boundary information plays a major role in developing such intelligent vehicles. A prominent feature of roads in urban, semi-urban, and similar environments, is curbs on either side defining the road's boundary. In this brief, a novel methodology of tracking curbs is proposed. The problem of tracking a curb from a moving vehicle is formulated as tracking of a maneuvering target in clutter from a mobile platform using onboard sensors. A curb segment is presumed to be the maneuvering target, and is modeled as a nonlinear Markov switching process. The target's (curb's) orientation and location measurements are simultaneously obtained using a two-dimensional (2-D) scanning laser radar (LADAR) and a charge-coupled device (CCD) monocular camera, and are modeled as traditional base state observations. Camera images are also used to estimate the target's mode, which is modeled as a discrete-time point process. An effective curb tracking algorithm, known as Curb Tracking and Estimation (CuTE) using multiple modal sensor information is, thus, synthesized in an image enhanced interactive multiple model filtering framework. The use and fusion of camera vision and LADAR within this frame provide for efficient, effective, and robust tracking of curbs. Extensive experiments conducted in a campus road network demonstrate the viability, effectiveness, and robustness of the proposed method. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Control Systems Technology	en_US
dc.relation.isbasedon	10.1109/TCST.2006.876929	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	CuTE: Curb Tracking and Estimation	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	14	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0102 Applied Mathematics	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 Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	14	en_US

Abstract:

The number of road accident related fatalities and damages are reduced substantially by improving road infrastructure and enacting and imposing laws. Further reduction is possible through embedding intelligence onto the vehicles for safe decision making. Road boundary information plays a major role in developing such intelligent vehicles. A prominent feature of roads in urban, semi-urban, and similar environments, is curbs on either side defining the road's boundary. In this brief, a novel methodology of tracking curbs is proposed. The problem of tracking a curb from a moving vehicle is formulated as tracking of a maneuvering target in clutter from a mobile platform using onboard sensors. A curb segment is presumed to be the maneuvering target, and is modeled as a nonlinear Markov switching process. The target's (curb's) orientation and location measurements are simultaneously obtained using a two-dimensional (2-D) scanning laser radar (LADAR) and a charge-coupled device (CCD) monocular camera, and are modeled as traditional base state observations. Camera images are also used to estimate the target's mode, which is modeled as a discrete-time point process. An effective curb tracking algorithm, known as Curb Tracking and Estimation (CuTE) using multiple modal sensor information is, thus, synthesized in an image enhanced interactive multiple model filtering framework. The use and fusion of camera vision and LADAR within this frame provide for efficient, effective, and robust tracking of curbs. Extensive experiments conducted in a campus road network demonstrate the viability, effectiveness, and robustness of the proposed method. © 2006 IEEE.

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http://hdl.handle.net/10453/5840