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A stochastic algorithm for obstacle motion prediction in visual guidance of robot motion

Qingqing Zhu

Year
2002
Citations
11

Abstract

The algorithm presented is based on a hidden Markov model description of the motions of obstacles and uses probabilistic evaluation for the selection of collision-free trajectories in the visual guidance of mobile robot motion. The algorithm is reliable in terms of catching the nature of obstacle motions in a dynamic environment. The computation time is modest, as the simulation results show

Keywords

ObstacleComputer scienceMobile robotMotion (physics)Probabilistic logicComputationComputer visionRobotArtificial intelligenceMarkov process

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