Simultaneous Mapping and Stereo Extrinsic Parameter Calibration Using GPS Measurements
Stereo vision is useful for a variety of robotics tasks, such as navigation and obstacle avoidance. However, recovery of valid range data from stereo depends on accurate calibration of the extrinsic parameters of the stereo rig, i.e., the 6-DOF transform between the left and right cameras. Stereo selfcalibration is possible, but, without additional information, the absolute scale of the stereo baseline cannot be determined. In this paper, we formulate stereo extrinsic parameter calibration as a batch maximum likelihood estimation problem, and use GPS measurements to establish the scale of both the scene and the stereo baseline. Our approach is similar to photogrammetric bundle adjustment, and closely related to many structure from motion algorithms. We present results from simulation experiments using a range of GPS accuracy levels; these accuracies are achievable by varying grades of commercially-available receivers. We then validate the algorithm using stereo and GPS data acquired from a moving vehicle. Our results indicate that the approach is promising.
Jonathan Kelly Larry H. Matthies Larry H. Matthies
Department of Computer Science,University of Southern California,Los Angeles,California 90089 Propulsion Laboratory,California Institute of Technology,Pasadena,California 91109
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
279-286
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）