Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

An extended robot–world and hand–eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot–world and hand–eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

Resection-Intersection Bundle Adjustment Revisited

Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation; only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.

The Calibration of Binocular Stereo Measurement System Based on a Coded Model

A calibration method of binocular stereo measurement system is proposed based on a coded model. Target points are designed to be with the unique IDs which make the match of two pictures and the match of image points and 3D points reliable and stable. The intrinsic parameters of the two cameras are calculated precisely and the 3D target point sets are reconstructed in each camera coordinate system respectively by using the multiple view geometry constraint and a generic sparse bundle adjustment. Then the extrinsic parameters are calculated by using the rigid transform of the two 3D point sets. The accuracy of the re-projection results is 0.037 pixel of standard error.

A Fast Orthoimage Mosaic Method for Application of Grid

Traditional orthoimage mosaic methods do not perform well in computational speed and geometric precision. This paper proposed a fast orthoimage mosaic method for the application of grid. First of all, down-sample the original images and extracts feature, and adopt SANSAC to estimate the relative initial homography; second, refine homography matrix by Levenberg-Marquardt method and use the sparse bundle adjustment method to estimate the precise homography matrix; Third, passed the homography matrix to the original level of image by the homography relationship of the down-sampling and original image. Finally, synthesize the mosaic image. Our experiments showed that the method combined the down-sampling homography relationship of original image with sparse bundle adjustment organically, which effectively improved the speed and obtained geometric seamless mosaic.