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