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Obstacle avoidance and path planning are the most important problems in mobile robots. Besides, finding methods for controlling and decreasing the real robot error in path have been another target for researchers investigation. Usual methods have two separated parts, research target and path planning with obstacle avoidance. In this context, a fuzzy logic controller has been constructed in order to...
In order to avoid obstacles efficiently and reach the goal quickly under multi-obstacle environment, we studied the path planning question of autonomous mobile robot (AMR) based on ultrasonic sensor information by combining genetic algorithm with fuzzy logic control. Firstly, the principles and configuration of ultrasonic sensors were introduced. Secondly, the dynamic model and kinetic equations of...
This paper proposes a sub-time-optimum soft-computing based controller to follow a desired path with a desired velocity by mobile robots with identified dynamical behavior. This method consists of a fuzzy controller where a trained neural network sets its membership functions values in on-line mode. Training of the network is done by a genetic algorithm for various vehicle initial positions and different...
The question concerned with how to guide an autonomous mobile robot (AMR) moving in obstructive environment to avoid obstacles and reach the goal was studied. Firstly, the dynamic equations of AMR were constructed. Secondly, according to the number of obstacles, the avoiding behavior was studied, and a path-planning algorithm based on fuzzy control was also proposed. The angle between the obstacle...
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