DocumentCode :
1844418
Title :
A new method for pose fitting from two 3D point sets and its application to robot localization
Author :
Zhuang, Hanqi ; Sudhakar, Raghavan ; Roth, Zvi S.
Author_Institution :
Robotics Center, Florida Atlantic Univ., Boca Raton, FL, USA
Volume :
1
fYear :
1996
fDate :
22-28 Apr 1996
Firstpage :
655
Abstract :
A single-stage linear method is devised in this paper to simultaneously fit rotation and translation (pose) parameters given two sets of 3-D point measurements. The necessary and sufficient conditions for the unique solution of the pose determination problem are stated. The computational complexity of the new algorithm is similar to the existing linear algorithms. However it offers a mechanism to incorporate the reliability of measurements and a procedure to implement the estimation recursively. Applications of the technique include localization of a robot in its environment and real-time estimation of object motion based on computer vision
Keywords :
Kalman filters; calibration; computational complexity; motion estimation; recursive estimation; robots; 3D point sets; computational complexity; computer vision; necessary and sufficient conditions; object motion; pose fitting; real-time estimation; robot localization; rotation; single-stage linear method; translation; unique solution; Application software; Computer vision; Electric variables measurement; Equations; Motion estimation; Quaternions; Recursive estimation; Robot kinematics; Robot localization; Rotation measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1050-4729
Print_ISBN :
0-7803-2988-0
Type :
conf
DOI :
10.1109/ROBOT.1996.503849
Filename :
503849
Link To Document :
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