Application of fuzzy logic for the solution of inverse kinematics and hierarchical controls of robotic manipulators

In this paper, hierarchical control techniques is used for controlling a robotic manipulator. The proposed method is based on the establishment of a non-linear mapping between Cartesian and joint coordinates using fuzzy logic in order to direct each individual joint. The hierarchical control will be implemented with fuzzy logic to improve the robustness and reduce the run time computational requirements. Hierarchical control consists of solving the inverse kinematic equations using fuzzy logic to direct each individual joint. A commercial Microbot with three degrees of freedom is utilized to evaluate this methodology. A decentralized fuzzy controller is used for each joint, with a Fuzzy Associative Memories (FAM) performing the inverse kinematic mapping in a supervisory mode. The FAM determines the inverse kinematic mapping which maps the desired Cartesian coordinates to the individual joint angles. The individual fuzzy controller for each joint generates the required control signal to a DC motor to move the associated link to the new position. The proposed hierarchical fuzzy controller is compared to a conventional controller. The simulation experiments indeed demonstate the effectiveness of the proposed method.