An Approach for Optimal Design of Robot Vision Systems

Xu, Kanglin

doi:10.5772/9304

Cited by 1 publication

(1 citation statement)

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“…In these methods, the position accuracy is improved by compensation methods based on experimental calibration measurements to identify the geometric parameters of robots. Error modeling is a major process of compensation, and methods for developing models have been presented, such as matrix differential, screw theory and so on [5][6][7][8]. The matrix differential method is applied to build error functions of the end-effector by calculations of matrix product and derivative, which is widely used presently.…”

Section: Introductionmentioning

confidence: 99%

Compensation for Geometric Parameter Errors of a Picking Manipulator

Yan

Zhao³

2012

AMR

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In order to enhance position accuracy of robots, the precise error model is established by applying homogeneous matrix without any differential or partial derivatives required in other methods. An articulated picking manipulator with four-degree-of-freedom is taken as example to analyze the position accuracy affected by errors of geometric parameters (link length, link offset and twist angle). Furthermore, an error compensation algorithm based on error model and inverse kinematics is proposed and applied to the picking manipulator. Experimental simulation was carried out for verifying the feasibility of the presented algorithm, and results show that the maximum position errors in x, y, z axis have declined from 3.2369mm, 9.5583mm, 1.002mm to 0.1334mm, -0.0488mm, -0.001mm after compensation, which could greatly improve the position accuracy of the picking manipulator.

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Section: Introductionmentioning

confidence: 99%