Configuration optimization method of cooperative target for pose estimation with monocular vision

The distributive configuration of cooperative target is one of the important factors affecting the accuracy of pose measurement with monocular vision. In this paper, we propose a cooperative target configuration optimization method based on particle swarm optimization (PSO) to achieve a more accurate pose solution. First, the mathematical relationship between the distributive configuration of cooperative targets and measurement accuracy is derived based on the Perspective-n-Point (PnP) principle, meanwhile, the necessity for the distributive configuration optimization of cooperative targets is also demonstrated. Then, with the help of a pose solving algorithm based on angle parameterization, the PSO is adopted to construct the objective function and design the corresponding parameters. Next, the global optimal distributive configuration of cooperative target can be obtained by multiple reiterative methods, and the mathematical relationship is given between the cooperative target distributive configuration and the pose solution error. Finally, the feasibility and effectiveness of our method are verified by simulation and physical experiments. Compared to the random or artificially set cooperative target configurations, the proposed optimal configuration method improves the accuracy of pose measurement by 20%.