Robot Head-Eye calibration using the Minimum Variance method

Solving the Robot-World/Hand-Eye Calibration Problem Using the Kronecker Product

“…There, it is shown that the solutions can be split into two categories: iterative and closed-form. The iterative solutions [2][3][4][5][6][7] are generally very accurate when compared to the closed-form solutions. However, they are based on numerical techniques that can be slow and are dependent on initial conditions.…”

Stereo Camera Head-Eye Calibration Based on Minimum Variance Approach Using Surface Normal Vectors

“…It is similar to hand-eye calibration, but we call it head-eye calibration for convenience. The proposed method is an extended variance minimization (ExtMinVar) approach, which reduces the computational demand compared to the original minimum variance (MinVar) approach [ 1 ]. MinVar optimizes its solution over all 3D points in all views, which causes high amounts of computation per iteration that accumulates throughout the optimization process.…”

“…The main contributions of this paper are as follows: proposal of a cost-effective head-eye calibration that is simpler than that of the previous work [ 1 ] based on the minimum variance (MinVar) method, introduction of a novel cost function to minimize the covariance between surface normal vectors, rather than 3D point sets, and validation of the proposed approach through simulations as well as real experiments. …”

Orthogonal dual tensor method for solving the A X = X B sensor calibration problem

“…The practical side of these type of solutions is usually linked with the hand-eye calibration problem. Until now, the methods proposed to solve this type of problem vary from dual quaternions to global polynomial optimization [8][9][10][11][12][13].…”