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We propose a calibration method for the six degrees of freedom (DOF) extrinsic pose of a 2D laser rangefinder mounted to a robot arm. Our goal is to design a system that allows on-site re-calibration without requiring any kind of special environment or calibration objects. By moving the sensor we generate 3D scans of the surrounding area on which we run a iterative closest point (ICP) variant to estimate the missing part of the kinematic chain. With this setup we can simply scale the density and format of our 3D scan by adjusting the robot speed and trajectory, allowing us to exploit the power of a high resolution 3D scanner for a variety of tasks such as mapping, object recognition and grasp planning. Our evaluation, performed on synthetic datasets as well as from real-data shows that the presented approach provides good results both in terms of convergence on crude initial parameters as well as in the precision of the final estimate.

Extrinsic Calibration of an Eye-In-Hand 2D LiDAR Sensor in Unstructured Environments Using ICP