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Incremental Light Bundle Adjustment: Probabilistic Analysis and Application to Robotic Navigation

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New Development in Robot Vision

Part of the book series: Cognitive Systems Monographs ((COSMOS,volume 23))

Abstract

This paper focuses on incremental light bundle adjustment (iLBA), a recently introduced [13] structureless bundle adjustment method, that reduces computational complexity by algebraic elimination of camera-observed 3D points and using incremental smoothing to efficiently optimize only the camera poses.We consider the probability distribution that corresponds to the iLBA cost function, and analyze how well it represents the true density of the camera poses given the image measurements. The latter can be exactly calculated in bundle adjustment (BA) by marginalizing out the 3D points from the joint distribution of camera poses and 3D points. We present a theoretical analysis of the differences in the way that light bundle adjustment and bundle adjustment use measurement information. Using indoor and outdoor datasets we show that the first two moments of the iLBA and the true probability distributions are very similar in practice. Moreover, we present an extension of iLBA to robotic navigation, considering information fusion between high-rate IMU and a monocular camera sensor while avoiding explicit estimation of 3D points.We evaluate the performance of this method in a realistic synthetic aerial scenario and show that iLBA and incremental BA result in comparable navigation state estimation accuracy, while computational time is significantly reduced in the former case.

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Authors and Affiliations

  1. College of Computing, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Vadim Indelman & Frank Dellaert

Authors
  1. Vadim Indelman
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  2. Frank Dellaert
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Correspondence to Vadim Indelman .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, University of South Florida, Tampa, FL, USA

    Yu Sun

  2. Electrical and Computer Engineering and NanoScience Technology Center, University of Central Florida, Orlando, FL, USA

    Aman Behal

  3. Dept. of Mech. and Automation Eng., Vocational Training Council of Hong Kong, Hong Kong, China

    Chi-Kit Ronald Chung

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Indelman, V., Dellaert, F. (2015). Incremental Light Bundle Adjustment: Probabilistic Analysis and Application to Robotic Navigation. In: Sun, Y., Behal, A., Chung, CK. (eds) New Development in Robot Vision. Cognitive Systems Monographs, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43859-6_7

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  • DOI: https://doi.org/10.1007/978-3-662-43859-6_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43858-9

  • Online ISBN: 978-3-662-43859-6

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