Kinematic Control of Redundant Robot Arms Using Neural Networks

5Robust Neural Controller Design for Robot Arm Control

5.1 Introduction

In recent years, robotic manipulators have been widely employed in industry for labor‐intensive and high‐accuracy operations. The current shortage of skilled labor and the aging population pose urgent demands for robotic manipulation, e.g. payload transport, welding, painting, and assembly. Among the broad categories of manipulators, redundant manipulators, which have more control degrees of freedom (DOFs) than desired, are advantageous for dextrous manipulations due to their redundancy in DOFs. In comparison with traditional manipulators without extra DOFs, redundant manipulators usually have more than one control solution for a specific task, and thus allow designers to exploit this feature to fulfil additional requirements, such as obstacle avoidance and control optimization, and thus have received intensive research in recent years.

The introduction of extra DOFs in redundant manipulators increases the capability and flexibility of robotic manipulation, but also sets challenges for the control design for efficient redundancy resolution in real time. Analytically, the joint velocity of a nonredundant manipulator can be expressed in terms of the inverse of its Jacobian matrix. This result extends to redundant manipulators by replacing the Jacobian matrix inverse with its pseudo‐inverse, as the Jacobian matrix in this situation is nonsquare [25]. From an optimization perspective, this solution is equivalent ...