Abstract

Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots (FWIDSMRs) due to the flexible allocation of multiple maneuver modes. To address this problem, this study proposes a novel multiple mode-based navigation system, which can achieve efficient motion planning and accurate tracking control. To reduce the calculation burden and obtain a comprehensive optimized global path, a kinodynamic interior-exterior cell exploration planning method, which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm, is designed. By utilizing the sampled subgoals and the constructed global path, local planning is then performed to avoid unexpected obstacles and potential collisions. With the desired profile curvature and preselected mode, a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following precision. The tracking controller design is achieved using the quadratic programming (QP) technique, and the primal-dual neural network optimization technique is used to solve the QP problem. Experimental results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.

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