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Learning the motion patterns of humans for predictive navigation

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2 Author(s)
Shu-Yun Chung ; Dept. of Mech. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Han-Pang Huang

To achieve fully autonomous mobile robot in crowded environments, an efficient and real-time motion planning is necessary. In this paper, an A*-based predictive motion planner is presented for navigation tasks. A generalized pedestrian motion model is also introduced in this paper. By understanding pedestrian motion patterns, the robot can further predict their motions and avoid the collision as early as possible. The simulations and experiments are also shown to validate the idea of this paper.

Published in:

Advanced Intelligent Mechatronics, 2009. AIM 2009. IEEE/ASME International Conference on

Date of Conference:

14-17 July 2009