Monocular vision pose determination-based large rigid-body docking method

Abstract

Large rigid-body automatic docking is a crucial but tough task in aerospace assembly. Traditional large rigid-body spacecraft assembly is achieved manually, which is limited by high labor-intensity, low assembly quality, and long assembly cycle. This study proposes the monocular vision pose determination-based large rigid-body automatic docking method (MVPDLD) in which targets with circular feature points are attached to the surfaces of both mobile and fixed rigid-bodies; Thus, the proposed monocular vision system can track the relative pose between them. The measured relative pose is converted into kinematic parameters for a lightweight five-degree-of-freedom pose adjustment mechanism (5-DOFPAM), which can be guided via monocular vision pose determination to adjust the mobile rigid-body’s pose and achieve accurate docking. The MVPDLD method was validated on real datasets. MVPDLD’s accuracy is similar to traditional methods but achieves accurate docking much quicker. It can replace traditional manual methods for the automatic docking of large rigid-bodies.