The physical coupling between robots has the potential to improve the capabilities of multi-robot systems in challenging manufacturing processes. However, the path tracking accuracy of physically coupled robots is not studied adequately, especially considering the uncertain kinematic parameters, the mechanical elasticity, and the built-in controllers of off-the-shelf robots. This paper addresses these issues with a novel differential-algebraic system model which is verified against measurement data from real execution. The uncertain kinematic parameters are estimated online to adapt the model. Consequently, an adaptive model predictive controller is designed as a coordinator between the robots. The controller achieves a path tracking error reduction of 88.6% compared to the state-of-the-art benchmark in the simulation.

翻译：机器人间的物理耦合有望提升多机器人系统在复杂制造工艺中的性能。然而，物理耦合机器人的路径跟踪精度尚未得到充分研究，特别是在考虑不确定运动学参数、机械弹性以及商用机器人内置控制器的情况下。本文通过提出一种经实际执行测量数据验证的新型微分代数系统模型来解决这些问题。模型通过在线估计不确定运动学参数实现自适应调整。在此基础上，设计了一种自适应模型预测控制器作为机器人间的协调器。仿真结果表明，该控制器相较于现有先进基准方法，将路径跟踪误差降低了88.6%。