This paper proposes a novel relative navigation control strategy based on the relation space method (RSM) for articulated\nunderground trackless vehicles. In the RSM, a self-organizing, competitive neural network is used to identify the space around the\nvehicle, and the spatial geometric relationships of the identified space are used to determine the vehicle�s optimal driving direction.\nFor driving control, the trajectories of the articulated vehicles are analyzed, and data-based steering and speed control modules\nare developed to reduce modeling complexity. Simulation shows that the proposed RSM can choose the correct directions for\narticulated vehicles in different tunnels. The effectiveness and feasibility of the resulting novel relative navigation control strategy\nare validated through experiments.
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