Design of Kinematic Controller Based on Parameter Tuning by Fuzzy Inference System for Trajectory Tracking of Differential-Drive Mobile Robot

2020 ◽  
Vol 22 (6) ◽  
pp. 1972-1978
Author(s):  
Tran Quoc Khai ◽  
Young-Jae Ryoo ◽  
Woo-Ram Gill ◽  
Dae-Yeong Im
2012 ◽  
Vol 151 ◽  
pp. 184-188 ◽  
Author(s):  
Muhammad Mahbubur Rashid ◽  
Amir Akramin Shafie ◽  
Tarik Bin Alamgir ◽  
Ibrahim Jawad Alfar

Tracking a person successfully and following robustly is a significant ability that requires to be overwhelmed by a service robot while it requires completing some human-related tasks. Such capability has desires, which cannot be met pleasingly using conventional numerical process. Most remarkably, the robot has to stay at a certain safe distance as of the person that is being tracked and simultaneously be in motion in a smooth way which does not seem to be frightening to the person. In this research, consequently, a Fuzzy Inference System (FIS) is developed and used as a controller to provide decisions achieving smooth and safe person-following activities. The Fuzzy system is made to work in combination with a Optoelectronic (IR) sensor detection algorithm which acquire the position in using co-ordinate system and the velocity of the person is detected by using ultrasonic sensor and these are used to generate the Fuzzy Inference System distance and velocity information necessary for the control process. The simulation and result on this research established that even though the detection of IR is subject to minor noise and false negatives, the robot will achieve the smoothness and safety objectives while following its target. An example with a mobile robot tracking a person demonstrates the performance of our approach.


Sign in / Sign up

Export Citation Format

Share Document