In this paper we address the problem of autonomous robot navigation in a "roadway" type environment, where the robot
has to drive forward on a defined path that could be impeded by the presence of obstacles. The specific context is the
Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The task of the path planner is to
ensure that the robot follows the path without turning back, as can happen in switchbacks, and/or leaving the course, as
can happen in dashed or single lane line situations. A multi-behavior path planning algorithm is proposed. The first
behavior determines a goal using a center of gravity (CoG) computation from the results of image processing techniques
designed to extract lane lines. The second behavior is based on developing a sense of the current "general direction" of
the contours of the course. This is gauged based on the immediate path history of the robot. An adaptive-weight-based
fusion of the two behaviors is used to generate the best overall direction. This multi-behavior path planning strategy has
been evaluated successfully in a Player/Stage simulation environment and subsequently implemented in the 2009 IGVC.
The details of our experience will be presented at the conference.
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