Probabilistic Rapidly-exploring Random Trees for autonomous navigation among moving obstacles
نویسندگان
چکیده
The paper presents a navigation algorithm for dynamic, uncertain environment. The static environment is unknown, while moving pedestrians are detected and tracked on-line. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles trajectory and the probability of collision is explicitly taken into account. The algorithm is used in a partial motion planner, and the probability of collision is updated in real-time according to the most recent estimation. Results show the performance for a car-like robot among a pedestrian tracking dataset and simulated navigation among multiple dynamic obstacles.
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In this document we address the problem of autonomous navigation in dynamic unknown environments. The key of the problem is to guarantee safety for all the agents moving in the space (people, vehicles and the robot itself) while moving toward a predefined goal. In contrast with static or controlled environments, high dynamic environments present many difficult issues: the detection and tracking...
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تاریخ انتشار 2009