Data Fusion Calibration for a 3D Laser Range Finder and a Camera using Inertial Data.

Abstract

Abstract — The use of 3D laser range �nder (LRF) and cameras is increasingly common in the navigation application for mobile robots. This paper proposes a new method to perform the extrinsic calibration between a pinhole camera and a 3D-LRF with the aid of an Inertial Measurement Unit (IMU). While state of the art calibration procedures require a large number of points for robust calibration, the proposed approach is innovate in terms of higher �exibility and wider range of application. The proposed method is based on the presentation to the sensor platform of a stationary planar board containing a checkerboard pattern. The homography which de�nes the rotation matrix between the LRF and camera is achieved moving the robot and observing the resulting motion of the sensors. This step attempts to solve the well-known homogeneous transform equation of the form AX = BX. Next, translation is calculated using a commonly least-squares estimation algorithm according to the corners of the pattern, previously detected by both, camera and LRF. The developed algorithm was tested on a mobile robot which is equipped with sensor platform composed of pinhole camera, LRF pan-tilt unit and a IMU, and proved to be very accurate. Furthermore, the applicability of the method is greatly expanded, requiring attachment of a simple inertial sensor to the sensor platform.