Extrinsic Calibration Methods for Laser Range Finder and Camera: A Systematic Review

Fusion of laser range finder (LRF) and camera is widely used in the field of intelligent mobile robots for performing various tasks, such as autonomous navigation, 2D or 3D mapping, object classification and obstacle avoidance. However, data misregistrations between both the sensors occur during installation. The extrinsic calibration (rotation and translation parameters) of these two different sensor modalities is an important prerequisite for robust data fusion. There are numerous techniques available for calibrating 2D-LRF and 3D-LRF with cameras, which can be methodologically distinguished based on target-based and target-less approaches, and these techniques can be further classified based on human interaction level into manual and automatic approaches. This paper presents a systematic literature review of existing methods and techniques for estimating extrinsic calibration parameters of LRF and camera relative to each other and also compares them. In addition to this, it also discusses various robot applications based on the fusion of LRF and camera, where calibration of these two sensors improves the fusion results and makes the robotic system reliable and efficient in accomplishing several challenging tasks.