An iterative algebraic approach to TCF matrix estimation

One of the greatest challenges in developing eye- in-hand visual servoing systems is accurate calibration. The central problem of eye-in-hand calibration is to solve the unknown extrinsic parameter X in the homogeneous equation AX = XB. A new formulation using algebraic rearrangement in combination with singular value decomposition is introduced to solve this classical problem. In addition, an iterative algorithm that reduces the error in the initial estimate is used to further improve the results. Experimental results both in simulation and with real data show the method to be easy to use, efficient and accurate. One of the greatest challenges in developing eye-in-hand visual servoing systems is accurate calibration. The central problem of eye-in-hand calibration is to solve the unknown extrinsic parameter X in the homogeneous equation AX = XB. A new formulation using algebraic rearrangement in combination with singular value decomposition is introduced to solve this classical problem. In addition, an iterative algorithm that reduces the error in the initial estimate is used to further improve the results. Experimental results both in simulation and with real data show the method to be easy to use, efficient and accurate.