Abstract

The research in improving the efficiency of the navigation of autonomous mobile robot is escalating in the field of robotics. Path planning and Obstacle avoidance are important aspects of autonomous mobile robot navigation. This requires highly accurate and robust sensors for ranging and obstacle detection. Error reduction in these sensors can be achieved using various statistical methods. The proposed technique for error reduction utilizes ANFIS system for reducing error in ultrasonic sensor and wheel speed encoder. The ANFIS models for the sensors are evaluated with different membership function for finding the one with the best RMSE. The trained ultrasonic sensor and wheel speed encoder are integrated with LiDAR, used for building an autonomous mobile robot.

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