Processing configuration off-line optimization for functionally redundant robotic drilling tasks

Abstract

As a key technology of robotic assembly system, off-line programming (OLP) is an effective way to improve processing quality and efficiency. Currently, the basic functions of OLP systems, such as trajectory planning, three-dimensional task simulation and collision detection, could not achieve high machining precision and guarantee the quality stability. Thus, robot kinematics and stiffness performance optimization need to be investigated as secondary tasks in the special OLP system, on the basis of redundant kinematics characteristic of a serial robot system with external axis. First, a singularity measurement model of robot configuration is presented under the constraint of joint-limits to achieve the avoidance of singular and joint-limits configurations. Secondly, based on the robot static stiffness model, an axial stiffness identification method has been come up with to evaluate the stiffness performance in the processing direction. Next, with the combination of singularity measurement model and axial stiffness identification method, a redundancy resolution method is put forward to plan and optimize the configuration of robot system with external axis off-line, which keeps robots away from singularity and joint-limits, and meanwhile achieve the optimum stiffness during robotic drilling process. Finally, the validity of this method in improving drilling quality and stability is verified by the application in a robotic drilling system.