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.
Bibliographical noteFunding Information:
This work was supported in part by the NRF, MSIP(NRF-2017R1A2A1A17069329), and also supported by the Agriculture, Food and Rural Affairs Research Center Support Program (Project No. 714002-07), Ministry of Agriculture, Food and Rural Affairs.
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
- Mobile robot
- Motion uncertainty
- Path planning
- Wheel encoder
ASJC Scopus subject areas
- Analytical Chemistry
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering