Motion Planning of Hyper-Redundant Manipulators Based on Ant Colony Optimization

This paper presents a new approach for motion planning of hyper-redundant manipulators to meet real time and high performance of the control system. In this research, the ant colony optimization (ACO) of rotation angle parameters was applied, to ensure the optimal performance in meeting varying the position of the end effector and the obstacles. Furthermore, collision check between the manipulator and obstacles is accomplished with the help of the geometrical method. In order to solve the problem of the minimum energy consumption, we present a motion planning optimization method based on the energy function of the manipulator. Moreover, to demonstrate the effectiveness of this proposed algorithm, we exemplify our algorithm on a 10 degrees of freedom (DOFs) hyper-redundant manipulator.