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Real-time self-reaction of mobile robot with genetic fuzzy neural network in unknown environment

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4 Author(s)
Ma Xiaowei ; Sch. of Mechatronic Eng., Harbin Inst. of Technol., China ; Li Xiaoli ; Ma Yulin ; Cai Hegao

Presents an intelligent control method for real-time self-reaction of a mobile robot in an unknown environment, it is called a genetic fuzzy neural network. It is used to control a mobile robot according to sensing different information, which includes the different direction distances between the obstacles and robot sensed by ultrasonic sensors, the target orientation sensed by a simple optical range-finder and the robot's direction of movement. In the paper, the distances dr, dc, and dl between the robot and the obstacles with respect to the right, front and left sensors, as well as the angle tr, between the target orientation and the robot's direction of movement are taken as the inputs of the intelligent controller. The output of the intelligent controller is the steering angle sa. A genetic fuzzy neural network is presented to describe the fuzzy reasoning relationship between the inputs and the output of the system. It has a few advantages, such as higher learning speed and easier ensuring convergence. Simulation results of mobile robot collision avoidance in an unknown environment show the method presented is feasible

Published in:

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on  (Volume:4 )

Date of Conference:

11-14 Oct 1998

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