ICRA 2012 Paper Abstract

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Paper WeC09.5

Maddern, William (Queensland University of Technology), Harrison, Alastair (University of Oxford), Newman, Paul (Oxford University)

Lost in Translation (and Rotation): Rapid Extrinsic Calibration for 2D and 3D LIDARs

Scheduled for presentation during the Regular Session "Visual Tracking" (WeC09), Wednesday, May 16, 2012, 15:30−15:45, Meeting Room 9 (Sa)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 18, 2018

Keywords Calibration and Identification, Field Robots, Mapping

Abstract

This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.

 

 

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