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Determining 3-D Relative Transformations for Any Combination of Range and Bearing Measurements | IEEE Journals & Magazine | IEEE Xplore

Determining 3-D Relative Transformations for Any Combination of Range and Bearing Measurements

Publisher: IEEE

Abstract:

In this paper, we address the problem of motion-induced 3-D robot-to-robot extrinsic calibration that is based on ego-motion estimates and combinations of interrobot meas...View more

Abstract:

In this paper, we address the problem of motion-induced 3-D robot-to-robot extrinsic calibration that is based on ego-motion estimates and combinations of interrobot measurements (i.e., distance and/or bearing observations from either or both of the two robots, recorded across multiple time steps). In particular, we focus on solving minimal problems, where the unknown 6-degree-of-freedom (DOF) transformation between the two robots is determined based on the minimum number of measurements necessary to find a finite set of solutions. In order to address the very large number of possible combinations of interrobot observations, we identify symmetries in the measurement sequence and use them to prove that any extrinsic robot-to-robot calibration problem can be solved based on the solutions of only 14 (base) minimal problems. Moreover, we provide algebraic (closed-form) and efficient symbolic-numerical (analytical) solution methods to these minimal problems. Finally, we evaluate the performance of our proposed solvers through extensive simulations and experiments.
Published in: IEEE Transactions on Robotics ( Volume: 29, Issue: 2, April 2013)
Page(s): 458 - 474
Date of Publication: 10 December 2012

ISSN Information:

Publisher: IEEE

I. Introduction

Multirobot systems have attracted considerable attention due to their wide range of applications, such as search and rescue [1], target tracking [2], cooperative localization [3], and mapping [4]. In order to accomplish these tasks cooperatively, it is necessary for the robots to share their sensor measurements. These measurements, however, are registered with respect to each robot's local reference frame and need to be converted to a common reference frame before they can be fused. Such a conversion requires the knowledge of the robot-to-robot transformation, i.e., their relative position and orientation (pose). Most multirobot estimation algorithms assume that this robot-to-robot transformation is known. However, only few works describe how to compute it.

References

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