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Hand-Eye Calibration of EOD Robot by Solving the AXB = YCZD Problem

Jianfeng Jiang, Xiao Luo, Shijie Xu, Qingsheng Luo, Minghao Li

Year
2021
Citations
10
Access
Open access

Abstract

The explosive ordnance disposal (EOD) robots work in a special environment, which requires dual robotic arms to work together for removing the bomb. Therefore, machine vision is very important to locating bombs, especially the accuracy of the hand-eye calibration technology. A basic problem encountered with the collaborative work of dual robotic arms is to solve the unknown homogeneous transformation matrix, including: hand-eye of robotic arm 1, base-base, and camera-end effector’s robotic arm 2. In this article, the hand-eye calibration problem of the dual robotic arm system is expressed as two matrix equations. A new method of simultaneously solving the unknowns in the matrix equation is proposed. This method consists of a closed-form method based on the Kronecker product and an iterative method that transforms a nonlinear problem with a convex function optimization problem. The closed-form method is used to quickly obtain the initial value of the iteration method to improve the efficiency and accuracy of the iteration. In addition, we propose a hand-eye calibration method based on the re-projection error of the RGB-D camera. In order to prove the feasibility and superiority in the proposed iterative method, we conducted simulation and actual experiments and compared them with the other two calibration methods. The comparison results verify the superiority in the proposed method in terms of accuracy.

Keywords

Computer scienceComputer visionArtificial intelligenceIterative methodTransformation matrixProjection (relational algebra)Robotic armCalibrationKronecker productMathematical optimization

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