Bias Estimation and Calibration of a Pair of Laser Range Sensors

Abstract

Abstract Laser range sensors (LRS) are ubiquitous in mobile robotics. They are usually modeled as having statistical error only, despite some having systematic error (bias) documented. This paper deals with bias estimation for laser range sensors in order to produce better calibration for two LRS. Assuming both LRS sense in the same plane, we propose an algorithm to estimate position and orientation of the second laser in the coordinate frame of the first laser, or vice versa. In order to truly have corresponding points in two LRS scans, we propose a calibration target. We use cylindrical objects of known radius, placed in the field of view of both LRS, perpendicularly to the sensing plane. Centers of circles that result from the intersection of the sensing plane and cylindrical objects then become corresponding points. Our algorithm first estimates cylinder centers, together with their respective uncertainties, and then using those results produces Euclidean transform estimate, together with it's respective uncertainty. The results of this algorithm can be used to gather very precise ground truth for people tracking applications with LRS. In case of occlusions, one has obvious benefits from two or more different viewpoints.