Beobot 2.0: Autonomous Mobile Robot Localization and Navigation in Outdoor Pedestrian Environment

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#ChinKai Chang #Christian Siagian #Laurent Itti #Beobot 2.0 #autonomous mobile robot #visionbased road recognition #USC #University of Southern California

This video shows Beobot 2.0 in action. It's a mobile robot navigation system developed at USC that's guided by a vision-based road recognition approach. The system represents the road as a set of lines extrapolated from the detected image contour segments. These lines enable the robot to maintain its heading by centering the vanishing point in its ?eld of view, and to correct the long term drift from its original lateral position. Odometry and the visual road recognition system is integrated into a grid-based local map that estimates the robot pose as well as its surroundings to generate movement path.

This video presents Beobot 2.0, an autonomous mobile robot designed to operate in unconstrained urban environments. Over the past two years, Beobot has successfully traversed various paths across the USC campus, recognizing and following different types of roads, avoiding obstacles such as pedestrians and service vehicles, and finding its way to the goal.

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