Title :
Road Following in an Unstructured Desert Environment Based on the EM(Expectation-Maximization) Algorithm
Author :
Lee, Jaesang ; Crane, Carl D., III
Author_Institution :
Center for Intelligent Machines & Robotics, Florida Univ., Gainesville, FL
Abstract :
This paper describes the development and performance of a vision system, named PFSS (path finder smart sensor) for autonomous navigation of an unmanned ground vehicle. A monocular camera and vision processing algorithms were used as the sensor system to identify traversable terrain. Unlike the Bayesian based method which was used by Team CIMAR in the 2005 DARPA Grand Challenge, the expectation-maximization (EM) algorithm is applied. The implementation and performance of this approach are reported here
Keywords :
cameras; expectation-maximisation algorithm; image segmentation; remotely operated vehicles; robot vision; sensors; Bayesian method; autonomous navigation; expectation-maximization algorithm; monocular camera; path finder smart sensor; road following; traversable terrain identification; unmanned ground vehicle; unstructured desert environment; vision processing algorithms; Cameras; Intelligent robots; Intelligent sensors; Intelligent vehicles; Machine vision; Navigation; Remotely operated vehicles; Road vehicles; Robot sensing systems; Robot vision systems; autonomous vehicle; expectation-maximization (EM) algorithm; image segmentation; navigation; vision system;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.314963
