GIS Ostrava 2021 – Advances in Localization and Navigation March 17–19, 2021 INTELLIGENT VELOCITY CONTROL OF MOBILE ROBOTS USING FUZZY AND SUPERVISED MACHINE LEARNING

This paper proposes an intelligent technique for velocity control of a wheeled mobile robot by simultaneously using a fuzzy controller and a supervised machine learning (SML) algorithm. The technique is suitable for flexible leader-follower formation control on straight paths where a follower robot maintains a safe but flexible distance from a leader robot. The fuzzy controller determines the ultimate distance of the follower with respect to the leader from the measurements of two ultrasonic sensors. The SML algorithm calculates an appropriate velocity for the follower based on the ultimate distance. Simulations showed the effectiveness of the proposed technique in adjusting the follower robot's velocity in order to maintain a flexible formation with the leader robot.