基于鱼眼相机和 RGBD 相机的异构协同 SLAM

SLAM technology has a the potential of wide applications in autonomous navigation in satellite navigation denied environments. To combine the advantages of monocular fisheye SLAM to obtain more texture information and RGBD-SLAM to directly obtain scale information，a heterogeneous collaborative SLAM system is designed based on a monocular fisheye camera and a RGBD camera. Firstly，a method for checking the 3D gray centroid direction consis⁃ tency between feature points is designed to screen the candidate matching points between heterogeneous images. Then，a step-by-step optical flow and projection matching method between heterogeneous images is designed to achieve high-performance feature point matching and relative pose estimation between fisheye and RGBD camera. Fi⁃ nally，based on the ORB-SLAM2 framework，a heterogeneous collaborative SLAM system is proposed based on fish⁃ eye and RGBD camera. The experimental results show that compared with traditional feature point matching meth⁃ ods，the proposed feature point matching method shows higher performance in the task of image feature matching with heterogeneous cameras. Compared with the monocular fisheye SLAM and RGBD-SLAM system，the proposed heterogeneous collaborative SLAM system has better performance under the conditions of rapid camera movement，camera close to the scene，low frame rate，texture loss，pure rotation of the camera，outdoor large scenes，etc. ，and demonstrates improved robustness，anti-drift ability and trajectory accuracy.