This paper presents and compares a set of calibration strategies useful to calibrate vision-based robotised work-cells for micromanipulation and microassembly. To grasp and release microparts precisely, robot calibration, camera calibration and robot-camera registration are needed. Conventional calibration methods are very onerous at the microscale, therefore, two alternative unconventional procedures, called virtual grid calibration and hybrid calibration, are developed for work-cells with high-performance robots, minimising necessary instrumentation. Moreover, an effective calibration of the robot end-effector is designed to compensate for misalignment and orientation errors with respect to the vertical rotational axis. This paper describes the calibration methods and their implementation, the results and the improvements achieved. A detailed comparison between the hybrid and the virtual grid calibrations is provided, demonstrating the higher performance of the latter strategy.

We consider the conventional techniques of vision robot system calibration where camera parameters and robot hand–eye parameters are computed separately, i.e., first performing camera calibration and then carrying out hand–eye calibration based on the calibrated parameters of cameras. In this paper we propose a joint algorithm that combines the camera calibration and the hand–eye calibration together. The proposed algorithm gives the solutions of the cameras' parameters and the hand–eye parameters simultaneously by using nonlinear optimization. Both simulations and real experiments show the superiority of our algorithm. We also apply our algorithm in the real application of the robot-assisted surgical system, and very good results have been obtained.

This work presents a methodology using image analysis to estimate the experimental stiffness of a parallel robot, Parallix LKF-2040, a 3-degree-of-freedom manipulator. The proposed methodology has a simple implementation and can be applied to different architectures of parallel robots. This methodology uses image analysis and camera calibration techniques to estimate compliant displacements of mobile platform produced by several loads at the end effector level, and calculate stiffness in a specific position of mobile platform. Experimental results are presented for different positions within the workspace.

A prototype system utilizing a vision technique to monitor the parameters of adhesive beads or sealants is presented. The system uses a structured light technique to investigate adhesive beads and extract information about the shape of the bead from binary images. The geometrical model of the bead, the relationship between this model and the shape of a line of light on the image are investigated. The models for calculating the parameters of the bead and the height of the camera are analyzed. Control strategies are suggested.