Path Planning of Mobile Robot Based on Improved APF-QRRT*Strategy
This paper presents an enhanced path planning strategy,namely Improved Artificial Potential Field-QRRT*(IAPF-QRRT*),to address the problem of the existing Q-RRT*algorithm in meeting both reachability and safety requirements during the path planning process.The IAPF-QRRT*strategy utilizes the Q-RRT*algorithm to obtain a set of critical discrete path points that connect the starting and ending points,which offers improved initial solutions and faster convergence speed compared with the traditional RRT*algorithm.Additionally,a novel non-potential orthogonal vector field is derived by enhancing the conventional Artificial Potential Field(APF)method.Under specific conditions,the repulsive vector field is orthogonal to the attractive vector field,thereby enhancing safety along the critical path points.Comparative analysis with other algorithms validates the effectiveness of the proposed IAPF-QRRT*strategy through numerical simulation experiments.
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