Trajectory planning of redundant manipulator using fuzzy clustering method

The solution of inverse kinematics and trajectory planning with performance criteria for a redundant manipulator is proposed with modification in fuzzy c-means. A new fuzzy clustering model based on a new generalized validity index based on weighted within-scatter metrics and between-cluster scatter metrics for the manipulator is proposed. In order to understand the proposed algorithm and to show its performance, two simulation studies of trajectory planning with manipulability criteria for a redundant manipulator are modeled to solve the problems of finding association rules in the data and of setting up an appropriate classification procedures. The problem of redundant manipulator (which is a multi-input, multi-output nonlinear system) is new in terms of solution by clustering method. The proposed algorithm for the trajectory planning of the manipulator is simulated using MatlabA (R). All practical steps, from data acquisition to model validation, are illustrated using a 4 degree of freedom robot manipulator. The simulated results are compared with the numerical methods of the trajectory planning. The results are presented graphically. The proposed method has the advantage of simplicity, flexibility, and good tracking performance.