Path Planning for Mobile Robot based on Autoregressive Model

Y. Mao, Y. Pang, Z. Wang, and T. Zhang (PRC)


Mobile robot, path planning, dynamic environment, and autoregressive


An uncertain environment path planning method for mobile robot in the presence of moving obstacles was designed in this paper. Combining the global planning with the local planning, this dissertation presents a new approach to on-line real-time path planning with respect to the dynamic uncertain environment. With current sampling position, the autoregressive model predicts motion trajectories of moving obstacles. And the predicted positions are treated as instantaneously static. So moving obstacles in the predicted positions can be considered as static in the path planning process. Simulation examples demonstrated the effectiveness, feasibility, real-time capability, high stability and perfect performance of obstacle avoidance.

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