Modeling and robust analysis of a fuzzy based person following robot

Ability to follow and track a person robustly is an essential prerequisite for human-robot-interaction. Such capability has desires, which cannot be met pleasingly using conventional numerical process. Most rigorously, the robot has to stay at a certain safe distance as of the person that is being tracked and concurrently be in motion smoothly which does not seem to be scary 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. Few approaches have been used to examine the performance of person following robot in smooth tracking and comparing and collating those ultimately an IR based co-ordinate system is used to obtain the tracking features for human robot interaction and the velocity of the person is detected by using ultrasonic sensor which are used to generate the Fuzzy membership function of FIS to control the robot movement. 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. In this paper robot modelling and its real time robust analysis is demonstrated for the designed prototype.