Relevant Work Published by the Author

This paper describes a new approach for approximating the inverse kinematics of a manipulator using a RBFN (Radial Basis Function Network). A training approach using the strict interpolation method and the LMS (Least Mean Square) algorithm is presented. The strict interpolation method with regularly spaced position training patterns in the workspace can produce an appropriate approximation of the inverse kinematic function. Additionally, the LMS algorithm can improve the approximate function iteratively through online training with arbitrary position patterns. The combination of these techniques can deal with variation in the set-up of the visual system used to measure the position of the manipulator in the workspace. To verify the performance of the proposed approach, a practical experiment has been performed using a Mitsubishi PA10-6CE manipulator observed by a webcam. The experimental results demonstrate that the proposed approach is effective. [2] B. H. Dinh, M. W. Dunnigan, D. S. Reay, “A Practical Approach for Position Control Of a Robotic Manipulator Using a RBFN and a Simple Vision System”, WSEAS Transactions on System and Control, Volume 3, Issue 4, April 2008, pp. 289-298. Abstract: This paper proposes a new practical approach using a RBFN (Radial Basis Function Network) to approximate the inverse kinematics function of a robot manipulator. It can be effectively applied for position control of a real robot-vision system in which robot movement in the workspace is observed by a camera. In fact, there are several traditional methods based on the known geometry of the manipulator to determine the relationship between the joint variable space and the world coordinate space. However, these traditional methods are impractical if the manipulator geometry cannot be determined This paper proposes a new practical approach using a RBFN (Radial Basis Function Network) to approximate the inverse kinematics function of a robot manipulator. It can be effectively applied for position control of a real robot-vision system in which robot movement in the workspace is observed by a camera. In fact, there are several traditional methods based on the known geometry of the manipulator to determine the relationship between the joint variable space and the world coordinate space. However, these traditional methods are impractical if the manipulator geometry cannot be determined