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Real-time tracking of an unpredictable target amidst unknown obstacles

Cheng‐Yu Lee, Héctor H. González-Baños, J.-C. Latombe

Year
2004
Citations
24

Abstract

This paper describes a new approach to keep a moving target into the field of view of a robot, despite obstacles. Unlike previous work, this approach does not assume that a complete or partial model of the target's behavior is available, nor that a map of the obstacles is given. At approximately 10 IIz, the robot constructs a local map of the environment from range data, localizes the target in this map, and computes its new velocity command. This command is selected to minimize a function that measures the risk that the target may escape the robot's field of view by crossing an occlusion ray created by an obstacle. The risk function defined in this paper combines a reactive term, whose minimization handles immediate threats, and a look-ahead term, whose minimization improves the robot's future ability to react to evading motions of the target. The experimental robotic system has been remarkably successful at tracking a target performing brisk maneuvers and swift turns behind obstacles.

Keywords

ObstacleRobotComputer scienceMinificationTracking (education)Computer visionMobile robotTrajectoryArtificial intelligenceTerm (time)

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