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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...
This paper presents a fuzzy logic controller tuned by genetic algorithm (GA) for path planning near the optimal time to avoid obstacles in unknown environments. A GA is applied to modify the input and output membership functions of the fuzzy controller. A Matlab application, Kiks II, is used to simulate a Khepera II robot. Also, this approach is implemented by Khepera II robot. It is also shown that...
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...
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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