Related Experiment Video
Updated: Jan 30, 2026

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection
Published on: February 7, 2025
Obstacle Avoidance of Two-Wheel Differential Robots Considering the Uncertainty of Robot Motion on the Basis of
1School of Mechanical Engineering, Korea University, Seoul 02841, Korea. jin8644@gmail.com.
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.
Related Concept Videos
The Uncertainty Principle
Uncertainty in Measurement: Reading Instruments
Frustration and Conflict: Avoidance-Avoidance, Double-Approach Avoidance
Uncertainty: Overview
Encoding
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
Uncertainty in Measurement: Significant Figures

