2.3AIOct 5, 2020
Fuzzy Approximate Reasoning Method based on Least Common Multiple and its Property AnalysisI. M. Son, S. I. Kwak, M. O. Choe
This paper shows a novel fuzzy approximate reasoning method based on the least common multiple (LCM). Its fundamental idea is to obtain a new fuzzy reasoning result by the extended distance measure based on LCM between the antecedent fuzzy set and the consequent one in discrete SISO fuzzy system. The proposed method is called LCM one. And then this paper analyzes its some properties, i.e., the reductive property, information loss occurred in reasoning process, and the convergence of fuzzy control. Theoretical and experimental research results highlight that proposed method meaningfully improve the reductive property and information loss and controllability than the previous fuzzy reasoning methods.
2.1ROApr 20, 2016
Position Prediction of Ball and Fuzzy Controller for Shooting Action in A Soccer Robot SystemGyongIl Ryang, MyongSong Choe, YongChol Sin
The robot soccer game based complex motion control has been widely studied for the moving object capture and shooting. A position prediction algorithm based on global vision is introduced in order to improve the accuracy and robustness of the vision system for tracking moving objects, including a Kalmanfiter, a dynamic window and an obstacle avoidance strategy. This paper deals with the positon prediction for moving ball by using Kalmanfiter and the Fuzzy Controller for shooting action in a dynamic environment.
3.9ROOct 26, 2015
Pan-Tilt Camera and PIR Sensor Fusion Based Moving Object Detection for Mobile Security RobotsYongChol Sin, MyongSong Choe, GyongIl Ryang
One of fundamental issues for security robots is to detect and track people in the surroundings. The main problems of this task are real-time constraints, a changing background, varying illumination conditions and a non-rigid shape of the person to be tracked. In this paper, we propose a solution for tracking with a pan-tilt camera and a passive infrared range (PIR) sensor to detect the moving object based on consecutive frame difference. The proposed method is excellent in real-time performance because it requires only a little memory and computation. Experiment results show that this method can detect the moving object such as human efficiently and accurately in non-stationary and complex indoor environment.