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21 March 2017 Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement
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Abstract
In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot’s actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2017/$25.00 © 2017 SPIE
Juqing Yang, Dayong Wang, Baixing Fan, Dengfeng Dong, and Weihu Zhou "Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement," Optical Engineering 56(3), 034111 (21 March 2017). https://doi.org/10.1117/1.OE.56.3.034111
Received: 21 November 2016; Accepted: 3 March 2017; Published: 21 March 2017
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