Robust Pose-Graph SLAM Using Absolute Orientation Sensing

abstract

• 2016 IEEE. It is known that in the simultaneous localization and mapping (SLAM) problem when a robot's orientation is known, an estimation of the history of its poses can be formulated as a standard linear least squares problem. In this letter, we exploit this property of SLAM to develop a robust pose-graph SLAM framework that uses absolute orientation sensing. Our contribution are as follows: 1) we show that absolute orientation can be estimated using local structural cues; and 2) we develop a method to incorporate absolute orientation measurements in both the front and back-end of pose-graph SLAM. We also demonstrate our approach through extensive simulations and a physical real-world demonstration along with comparisons against existing state-of-the-art solvers that do not use absolute orientation.

authors

• Chakravorty, Suman

published proceedings

• IEEE ROBOTICS AND AUTOMATION LETTERS

altmetric score

• 1

author list (cited authors)

• Agarwal, S., Parunandi, K. S., & Chakravorty, S.

citation count

• 5

complete list of authors

• Agarwal, Saurav||Parunandi, Karthikeya S||Chakravorty, Suman

publication date

• April 2019

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Robotics and Automation Letters  Journal

keywords

• LOCALIZATION
• Mapping
• Range Sensing
• Slam
• Visual-based Navigation

Digital Object Identifier (DOI)

• 10.1109/LRA.2019.2893436

start page

• 981

end page

• 988

volume

• 4

issue

• 2

URL

• http://dx.doi.org/10.1109/lra.2019.2893436