Advanced fuzzy logic control of a model car in extreme situations
Fuzzy Sets and Systems
An algorithm for planning collision-free paths among polyhedral obstacles
Communications of the ACM
Fuzzy Sets and Systems
Determining 3-D location parameters of a cylindrical object
Mathematical and Computer Modelling: An International Journal
Autonomous robot navigation using adaptive potential fields
Mathematical and Computer Modelling: An International Journal
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In this paper, a path planning method using fuzzy logic control and potential field for an Automatic Guided Vehicle (AGV) is proposed. The design and implementation of an AGV prototype are also presented. Prom a top-view image of an environment, the chamfer distance transform is used to build the artificial potential field required. The potential field method is used to calculate the repulsive force between the vehicle and the closest obstacle, and the attractive force generated by the goal. Then the resultant force guides the mobile vehicle to its destination. When trap situations occur and the AGV may not reach the goal or even collide the obstacles, a fuzzy logic controller is proposed to modify the direction of the AGV. Based on the angle between the obstacle and the goal, and the status of the AGV, a correction angle is generated by the simple fuzzy rules. Fuzzy logic control with the characteristic of simulating human thinking renders the path of the AGV smoother and safer. A prototype of the experimental AGV is built by modifying a consumer model car. The built mobile vehicle is shown to track the desired trajectories successfully according to the path planning algorithm we proposed. A series of simulations, based on window-frame type environments with geometric obstacles, show that the fuzzy logic control is able to make the AGV escape from trap situations and generate a smoother and safer trajectory.