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23 January 1997 STARLITE: a steering autonomous robot's lane investigation and tracking element
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The problem of determining the offset to lane markings is an important one in designing vision-based automotive safety systems that operate on structured road environments. The lane offset information is critical for lateral control of the automobile. In this paper, we investigate the use of this information for an autonomous robot's lane-keeping task. We employ a deformable template-based algorithm for determining the location of lane markings in visual images taken from a side-looking camera. The matching criteria involves a modification of the standard signal-to-noise (SNR) ratio-based matched filtering criteria. A KL-type color transformation is used for transforming the RGB channels of the given image onto a composite color channel, in order to eliminate some of the noise. The standard perspective transformation is used for transforming the offset information from image coordinates onto ground coordinates. The resulting algorithm, named STARLITE is robust to shadows, specular reflections, road cracks, etc. Experimental results are provided to illustrate the performance of STARLITE and compare its performance to the AURORA algorithm, and the SNR-based matched filter.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Randall DeFauw, Sridhar Lakshmanan, Natarajan Narasimhamurthi, Michael Beauvais, and Karl C. Kluge "STARLITE: a steering autonomous robot's lane investigation and tracking element", Proc. SPIE 2903, Mobile Robots XI and Automated Vehicle Control Systems, (23 January 1997);


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