Relative pose estimation of cooperative target based on monocular vision

Abstract

Abstract With the vigorous development of the global logistics industry, warehousing automation has become a popular applied research direction in computer vision. In this paper, the fork and the fork hole’s relative posture during the forklift picking process were taken as the research object. The relative position of the two is solved based on the Aruco cooperative logo PnP algorithm. In this paper, the initial values of the relative poses of the two are addressed by the linear algorithm DLT, and the relative poses are further optimized by Bundle Adjustment (BA). The iterative error observation function is constructed based on the visual pose estimation model, and the Gauss-Newton method is adopted. The least-square fitting iterative process is carried out many times, and the relative position and posture of the fork and the fork hole with high precision are finally obtained.