In robot grinding tasks, dual manipulators possess improved flexibility, which can cooperate to complete different tasks with higher efficiency and satisfactory effect. In collaborative robot grinding tasks, the critical issues lie in the motion trajectory planning of the two manipulators and trajectory tracking with satisfactory accuracy under the condition that the two manipulator ends apply force on each other. In order to accomplish the goals in a more concise and feasible way, a complete scheme for dual-arm robot grinding tasks is essential. To address this issue, taking the motion trajectory planning and impedance control into consideration, a novel scheme for dual manipulators to complete collaborative grinding tasks is presented in this paper. To this end, a dual-arm grinding system is first constructed, and the kinematic constraints in the cooperative motion are analyzed, based on which the motion trajectories of the dual manipulators are planned according to the grinding task objectives. Then, an impedance controller is designed to achieve accurate tracking of the motion trajectory in the grinding process. Finally, dual-arm collaborative simulations and grinding experiments are carried out, and the results show that the proposed method can achieve good motion results and better flexibility compared to the single-arm motion, which demonstrates the effectiveness of the proposed method.

Robot control based on visual information perception has been a hot topic in the field of industrial robots, and the use of visual servoing technology to guide robots for high-precision spatial localization of machined workpieces has a wide range of application value. Aiming at the camera hand–eye calibration error and robot repositioning error, which have a large impact on the spatial localization and navigation accuracy, and when the binocular camera Z-direction accuracy is not high enough and the viewing angle is limited, etc., we propose a spatial visual servoing algorithm based on an orthogonal vision system that combines an eye-in-hand camera and an eye-to-hand camera in a hybrid configuration. By extracting sub-pixel image features in real time and deriving directionally decoupled interaction matrices, a linear controller is designed to guide the robot in the XY-plane and Z-direction separately. This decoupling strategy enlarges the convergence domain, avoids local minima caused by coupled degrees of freedom, and enhances system stability. To this end, the intrinsic calibration and hand–eye calibration of two cameras placed orthogonally are carried out firstly, and the accuracy of hand–eye calibration is not too demanding; then the sub-pixel level image position of the target is extracted in real time and the interaction matrix is derived and a linear controller is designed to control the robot’s motion; finally, the experiments of spatial localization accuracy are completed on the KUKA iiwa to validate the effectiveness of the method.