To address the problem of high-precision autonomous visual positioning of asteroid probes, this paper proposes an autonomous visual positioning method for deep space probes incorporating orbital dynamics, which can correct the positioning errors of the simultaneous localization and mapping (SLAM) algorithm. The method enables high-precision visual navigation of the probe and the creation of a dense 3D model of the asteroid surface in a scenario, where there is no prior information on the surface and no manual markers by incorporating orbital dynamics for orbit improvement. Firstly, the visual simultaneous localization and mapping method (VSLAM) is used to extract the asteroid surface features, estimate the probe attitude utilizing a factorisation algorithm, and design loopback detection to improve the localisation accuracy. Secondly, we reconstruct the 3D model of the surface of the planet and realise the irregular gravitational field modelling of the planet based on the polyhedral method. Finally, a pseudo-relative motion orbit optimisation algorithm based on orbital dynamics is proposed as a physical constraint to correct the accumulated visual positioning error, and the propagation process of the inverse visual initial orbiting error in orbital dynamics is analysed to correct the accumulated visual positioning error and improve the initial positioning results. The experimental simulation results show that the fused orbital dynamics can effectively improve the accuracy of visual positioning for asteroid detection, thus realising high-precision navigation and providing a reference for the future development of deep space exploration technology.