Lost in translation (and rotation) : rapid extrinsic calibration for 2D and 3D LIDARs
Maddern, William, Harrison, Alistair, & Newman, Paul (2012) Lost in translation (and rotation) : rapid extrinsic calibration for 2D and 3D LIDARs. In Papanikolopoulos, Nikos (Ed.) Proceedings of the 2012 IEEE International Conference on Robotics and Automation, IEEE, River Center, Saint Paul, Minnesota, pp. 3096-3102.
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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|Item Type:||Conference Paper|
|Keywords:||Calibration , Cost function, Entropy, Laser radar, Sensors, Vehicles|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2012 IEEE|
|Deposited On:||10 Jul 2012 23:07|
|Last Modified:||12 Jun 2013 14:55|
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