Intelligent Control of a Miniature Climbing Robot
Jizhong Xiao*, Jun Xiao**, and Ning Xi***
*Dept. of Electrical Engineering, The City College, City University of New York, NY 10031, U.S.A.
**School of Information Science and Engineering, Northeastern University, Shenyang, China 110004
***Dept. of Electrical and Computer Engineering, Michigan State University, MI 48824, U.S.A.
This paper presents an intelligent control system of a miniature climbing robot to achieve precise motion control, minimize power consumption, and produce versatile behaviors. The gravitational effects degrade the motion control performance and are difficult to compensate exactly, especially in the case of the climbing robot. A fuzzy logic based control scheme is developed which is capable of compensating the gravity at different robot configurations and task conditions. In order to reduce power consumption, an optimal control law is developed which minimizes the energy used to vacuum the suction foot. Primitive behaviors are implemented to provide the robot with basic competence. A finite state machine (FSM) is developed to synthesize signals from multiple sensors, keep track of robot motion status, and schedule motion sequences. FSM is an effective computational method in behavior-based control paradigm to implement robot behaviors. Experimental results prove the validity of the proposed methods.