The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 89-741
Full Name: Mao Jianfei
Position: Associate Professor
Age: ON
Sex: Male
Address: Institute of Computer Science and Technology,Zhejiang University,Hangzhou, China
Country: CHINA
Tel: 13116788140
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Fax:
E-mail address: mjf@zjut.edu.cn
Other E-mails: zdmjf@yahoo.com.cn
Title of the Paper: a direct linear solution with jacobian optimization to ax=xb for hand-eye calibration
Authors as they appear in the Paper: Mao Jianfei,Tian Qing,Liang Ronghua
Email addresses of all the authors: mjf@zjut.edu.cn,tianqing@zjut.edu.cn,rhliang@zjut.edu.cn
Number of paper pages: 10
Abstract: A linear closed-form solution followed by Jacobian optimization is proposed to solve AX=XB for hand-eye calibration. Our approach does not require A,B satisfying rigid transformation rather than the classic ones based on quaternion algebra or screw rule. We firstly give the detailed proof of the optimal orthonormal estimation for an arbitrary scale matrix. With the theorem, a linear closed solution based on singular value decomposition (SVD) and the rule of optimal rotation estimation, is presented, followed by the nonlinear optimization with the proposed Jacobian recursive formula. Detailed deduction and demonstration are given based on matrix theory. Since our approach is applicable for non-rigid transformation rather than the classic ones, our technique is more flexible. Plenty of computer simulation and real data implementation indicate that: (1) In computation of initial value, our technique has higher precision and more robustness. (2) As more equations are !
added, initial value will converge to final value gradually, which shows it credible to regard initial value as final solution when many equations are supplied.
Keywords: closed-form solution,Jacobian optimization,hand-eye calibration,orthonormal estimation,SVD
EXTENSION of the file: .pdf
Special (Invited) Session: a flexible solution to ax=xb for robot hand-eye calibration
Organizer of the Session: 637-313
How Did you learn about congress: csy@zjut.edu.cn
IP ADDRESS: 60.176.65.30
