This paper presents an adaptive admittance control to achieve human-robot collaborative (HRC) assembling of large, heavy components without using external sensors. This sensorless adaptive admittance control is constructed by the dynamic model of a six degree-of-freedom (DoF) parallel robot based on finite and instantaneous screw (FIS) theory. The dynamic model is intuitive and easy to be programmed. After getting stable actuation force by Kalman filter and identifying friction by LuGre model, accurate force estimator is built. Admittance controller is adopted to convert the change of estimated force to the change in position, velocity and acceleration. As a result, the 6-DoF parallel robot is capable of following the guidance of operator. Particularly, adaptive admittance control is design by using robot velocity as reference. A fast motion before contacting and a fine motion during contacting are allowed. Experiments are conducted to verify force estimator, admittance control and adaptive admittance control for HRC assembly. Results show that external force is accurately estimated. Robot complaint control in response to operator's force is achieved. The adaptive admittance control enhances execution time, accuracy of the HRC assembly.

中文翻译：

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人机协同装配中六自由度并联机器人无传感器导纳控制

本文提出了一种自适应导纳控制，可在不使用外部传感器的情况下实现大型重型部件的人机协作（HRC）组装。这种无传感器自适应导纳控制是通过基于有限瞬时螺杆（FIS）理论的六自由度（DoF）并联机器人动力学模型构建的。动态模型直观且易于编程。通过卡尔曼滤波器获得稳定的驱动力并通过LuGre模型识别摩擦力后，建立了精确的力估计器。采用导纳控制器将估计力的变化转换为位置、速度和加速度的变化。因此，六自由度并联机器人能够遵循操作员的指导。特别地，以机器人速度为参考设计自适应导纳控制。允许接触前的快速运动和接触期间的精细运动。进行实验验证 HRC 装配的力估计器、导纳控制和自适应导纳控制。结果表明，外力的估计是准确的。实现了机器人响应操作者的力的投诉控制。自适应导纳控制提高了 HRC 装配的执行时间和精度。