Abstract
It is important to overcome different types of uncertainties for the safe and reliable navigation of mobile robots. Uncertainty sources can be categorized into recognition, motion, and environmental sources. Although several challenges of recognition uncertainty have been addressed, little attention has been paid to motion uncertainty. This study shows how the uncertainties of robot motions can be quantitatively modeled through experiments. Although the practical motion uncertainties are affected by various factors, this research focuses on the velocity control performance of wheels obtained by encoder sensors. Experimental results show that the velocity control errors of practical robots are not negligible. This paper proposes a new motion control scheme toward reliable obstacle avoidance by reflecting the experimental motion uncertainties. The presented experimental results clearly show that the consideration of the motion uncertainty is essential for successful collision avoidance. The presented simulation results show that a robot cannot move through narrow passages owing to a risk of collision when the uncertainty of motion is high. This research shows that the proposed method accurately reflects the motion uncertainty and balances the collision safety with the navigation efficiency of the robot.
Highlights
It is important to overcome different types of uncertainties for the safe and reliable navigation of mobile robots
A new motion control scheme toward reliable obstacle avoidance by reflecting the experimental motion uncertainties was proposed. It was shown how the uncertainty of robot motions can be quantitatively modeled based on the performance of the velocity control of a wheel
A controller was proposed where obstacles are extended as much as the motion uncertainty modeled in the input space
Summary
It is important to overcome different types of uncertainties for the safe and reliable navigation of mobile robots. Some obstacle avoidance schemes quantitatively consider the risk of collision. Chung proposed the collision risk index (CRI) that represents the margin of velocity control in the input space [14]. Previous research included the extension of the obstacle area to reduce the risk of collision It is useless for the performance and usability of the robot if the robot is moved by excessively expanding obstacles. The motion uncertainty is assumed to be represented by the velocity control error of a wheel. It is difficult to obtain conventional collision avoidance algorithms that explicitly consider the motion uncertainty of a robot. The velocity control error obtained by an encoder sensor is assumed to be a dominant source of motion uncertainty. The velocity control error of both wheels represents the motion uncertainty of a two-wheeled differential robot. The motion uncertainty of a robot can be obtained through practical experiments
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