Abstract
As the application of industrial robots is limited by low stiffness that causes low precision, a joint stiffness identification algorithm for serial robots is presented. In addition, a deformation compensation algorithm is proposed for the accuracy improvement. Both of these algorithms are formulated by dual quaternion algebra, which offers a compact, efficient, and singularity-free way in robot analysis. The joint stiffness identification algorithm is derived from stiffness modeling, which is the combination of the principle of virtual work and dual quaternion algebra. To validate the effectiveness of the proposed identification algorithm and deformation compensation algorithm, an experiment was conducted on a dual arm industrial robot SDA5F. The robot performed a drilling operation during the experiment, and the forces and torques that acted on the end-effector (EE) of both arms were measured in order to apply the deformation compensation algorithm. The results of the experiment show that the proposed identification algorithm is able to identify the joint stiffness parameters of serial industrial robots, and the deformation compensation algorithm can improve the accuracy of the position and orientation of the EE. Furthermore, the performance of the forces and torques that acted on the EE during the operation were improved as well.
Highlights
The robot can perform many tasks in order to help human beings in industrial fields
In order to verify the effectiveness of the stiffness identification algorithm and the deformation compensation algorithm presented above, a real experiment has been conducted on an industrial robot
The subject of this paper was to present a methodology for the joint stiffness identification of serial industrial robots based on dual quaternion algebra, which can express the displacement of the EE in a compact and efficient form
Summary
The robot can perform many tasks in order to help human beings in industrial fields. For example, machining and welding are classical. Lots of attention has been directed at studying the factors that influence the accuracy of the EE and how to deal with these issues [1,2] One solution to this problem is to identify the stiffness parameters of the industrial robot and use the deformation compensation algorithm to improve the performance of the robot’s tasks. Shin et al studied the stiffness model of redundant parallel kinematic mechanisms (PKM) and presented a decoupling method for explicit stiffness analysis of redundant PKM After that, they discussed the optimization and control of the PKM when external forces were applied to the mechanisms [19].
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