Much of our localisation, perception and mapping work uses multiple sensors. Sometimes we are talking about simple sets of cameras but frequently we are dealing with combinations of inertial, laser and camera sensors. These sensors are deployed across the physical vehicle and we cannot a-priori be sure of their exact location relative to each other.  This is a problem because without  very accurate knowledge of this spatial calibration we cannot hope to leverage the advantages of multiple sensor perception.

There is also the issue of temporal calibration  – how do we figure out the time lags between multiple sensors and how do we figure out the rate of change of those lags?

These spatial and temporal calibration tasks are vital to our endeavour.  We need to be able calibrate any set of sensors and to do so on a continual basis  – we call this life-long calibration. We do not want to calibrate just once and hope for the best for all time to come. We want to be continually watching for opportunity  to improve our calibrations and spot changes in them.


Our latest research

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

Abstract—This paper describes a novel method for deter- mining 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 ...
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Cross-Calibration of Push-Broom 2D LIDARs and Cameras In Natural Scenes

Abstract— This paper addresses the problem of automatically estimating the relative pose between a push-broom LIDAR and a camera without the need for artificial calibration targets or other human intervention. Further we do not require the sensors to have an ...
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TICSync: Knowing When Things Happened

Modern robotic systems are composed of many distributed processes sharing a common communications infrastructure. High-bandwidth sensor data is often collected on one computer and served to many consumers. It is vital that every device on the network agrees on how ...
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Self-calibration for a 3D laser

Abstract—This paper describes a method for the automatic self-calibration of a 3D Laser sensor. We wish to acquire crisp point clouds and so we adopt a measure of crispness to capture point cloud quality. We then pose the calibration problem ...
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Automatic Self-Calibration Of A Full Field-Of-View 3D n-Laser Scanner

Abstract - This paper describes the design, build, automatic self-calibration and evaluation of a 3D Laser sensor using conventional parts. Our goal is to design a system, which is an order of magnitude cheaper than commercial systems, with commensurate performance. In ...
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