In this paper I describe a motion planning technique for intelligent ground vehicles. The technique is an implementation of a path selection algorithm based on fuzzy inference. The approach extends on the motion planning algorithm known as driving with tentacles. The selection of the tentacle (a drivable path) to follow relies on the calculation of a weighted cost function for each tentacle in the current speed set, and depends on variables such as the distance to the desired position, speed, and the closeness of a tentacle to any obstacles. A Matlab simulation and the practical implementation of the fuzzy inference rule on a Clearpath Husky robot within the Robot Operating System (ROS) framework are provided.
Worcester Polytechnic Institute
Electrical & Computer Engineering
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Wang, Shiwei, "Motion Control for Intelligent Ground Vehicles Based on the Selection of Paths Using Fuzzy Inference" (2014). Masters Theses (All Theses, All Years). 725.
motion control, path planning, Matlab simulation, fuzzy inference, unmanned ground vehicle, robot operating system