Optimization of Biped Gait Synthesis Using Fuzzy Neural Network Controller

The Biped Robots have specific dynamical constraints and stability problems, which reduce significantly their motion range. In these conditions, path planning and tracking becomes very important. The joint profiles have been determined based on constraint equations cast in terms of step length and high, step period, maximum step height etc. In this paper Fuzzy Neural Network Controller for Path-Planning and Tracking on incline terrain (up stairs) of a planar five-link Biped Robot is presented. The locomotion control structure is based on integration of kinematics and dynamics model of Biped Robot. The proposed Control Scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on Biped Robot. Structure of Fuzzy Neural Network Controller is optimized using Genetic Algorithm. The effectiveness of the method is demonstrated by simulation example using Matlab software.