Synergetic Control System for Multi-Robot Assembly Based on Multisource Heterrogeneous Information Fusion

To realize the synergetic control between two robots, a synergetic control system combining with multisource heterogeneous information fusion is proposed in this paper. Firstly, the same type information in multi-robot, such as displacement, velocities, et al., are merged by using predictive Kalman filtering method. By using Taylor series expansion equation, the iterative sensing information is modified, and the state covariance is updated. Secondly, according to the distribution of space, function, and time, the heterogeneous information fusion method is used to improve the flexibility and robustness of the multi-robot synergetic assembly system. The iterative least square estimation algorithm is adopted. Numerical simulation results are reported to demonstrate the effectiveness of the proposed method.