A second-order conic optimization-based method for visual servoing

This work presents a novel method for the visual servoing control problem based on second-order conic optimization. Special cases of the proposed method provide similar results as those obtained by the position-based and image-based visual servoing methods. The goal in our approach is to minimize both the end-effector trajectory in the Cartesian space and image feature trajectories simultaneously. For this purpose, a series of second-order conic optimization problems is solved. Each problem starts from the current camera pose and finds the camera velocity as well as the next camera pose such that (1) the next camera pose is as close as possible to the line connecting the initial and desired camera poses, and (2) the next feature points are as close as possible to the corresponding lines connecting the initial and desired feature points. To validate our approach, we provide simulations and experimental results for several different camera configurations.