随着我国载人航天工程等重大项目的实施，传统以加工中心等专用机床为核心的加工手段已经无法适应当前航天器舱体等的大型复杂构件日趋大型化、复杂化的发展趋势。采用“工件不动+加工装备移动”的多机器人协同“原位加工”模式，因其工作空间、灵活性、协作模式以及作业能力等方面的优势，为大型复杂构件的高精度加工提供了新思路。本文以航天器大型复杂构件多机器人系统在“原位加工”模式下的应用为背景，提出了基于任务优先级法的移载机器人运动控制策略，有效提升了移载机器人一体化作业运动规划的刚度性能；提出了基于交叉耦合误差模型的鲁棒协同定位控制算法，实现了单机定位误差与双机协同定位误差同步收敛；提出了面向动态目标连续跟踪的视觉伺服双机器人协同轨迹跟踪控制方法，提升了连续运动过程中的双机器人的协同轨迹跟踪精度；搭建了基于分层式结构的视觉伺服双机器人协同加工系统，实现了双机器人协同高精度定位/轨迹跟踪控制方法在制孔和铣削上的应用。主要研究内容和取得成果如下：

（1）研究了“AGV移载平台+工业机器人”移载机器人一体化作业性能评价方法，提出了包括灵巧性能、重心稳定性等的性能评价指标，在此基础上分析了移载机器人连续运动过程中加速度层连续条件下的关节空间物理约束条件。结合系统连续运动过程中的机器人刚度性能评价指标，利用任务优先级法将作业过程中的系统速度层约束、灵巧性能约束等进行分层运动规划。仿真结果显示该方法能够在满足关节速度层物理约束的条件下，提升连续作业过程中的刚度性能。

（2）针对双机器人协同作业过程中“点到点”高精度定位需求，探究了双机器人协同运动过程中一致性误差的产生及叠加原理，提出了交叉耦合视觉伺服双机器人协同鲁棒控制方法。针对双机器人协同定位过程中的随机产生的单机及双机一致性误差，建立基于虑及双侧单机误差的交叉耦合一致性误差模型，设计面向单机误差和一致性误差同步收敛的鲁棒控制器，试验结果证明协同控制方法能够实现协同定位精度0.15 mm。

（3）针对双机器人协同作业过程中的连续轨迹跟踪需求，提出了双机器人连续目标动态跟踪视觉伺服协同控制方法。提出了一种三阶双目标位姿平滑估计算法，降低了末端执行器高速运动轨迹跟踪过程中的测量噪声，为双侧末端执行器连续轨迹跟踪运动过程中的高精度位姿测量及跟踪打下了基础。提出了一种针对连续轨迹动态跟踪的双机器人交叉耦合鲁棒控制方法，试验结果证明其协同轨迹跟踪精度可达0.2 mm。

（4）搭建了基于“IPC+实时工业现场总线”总体框架的大场景视觉伺服双机器人协同制孔/铣削加工系统，开展了双机器人协同加工试验，验证了基于双目视觉引导的大视场双机器人协同加工方法对于提升大型舱体构件关联安装支架一致性加工精度的有效性。

本文从移载机器人一体化作业运动控制和双机器人视觉伺服协同控制两方面开展了深入研究，在理论层面提出了面向作业刚度性能最优的移载机器人一体化运动控制方法和基于交叉耦合误差模型的双机器人协同视觉伺服高精度控制方法，在应用层面基于自主研发的双机器人视觉伺服协同加工系统完成了舱体模拟件表面关联尺寸支撑支架的协同加工任务。本文研究成果推动了以多机器人为载体的“原位加工”模式在航空航天先进装备制造业中的应用，具有重要的理论指导意义与工程应用价值。

With the launch of major projects such as China’s manned spaceflight project, the processing methods centered on special machine tools such as machining centers have been unable to adapt to the increasingly large and complex development trend of large and complex components such as spacecraft cabins. The multi-robot collaborative “in-situ processing” mode of “workpiece stationary + processing equipment movement” provides a new idea for the high-precision processing of large and complex components. This article takes the application of multi-robot system for large and complex components of spacecraft in “in-situ processing” mode as the background, proposes a mobile robot motion control method based on task priority method, effectively improves the stiffness performance of mobile robot integrated operation motion planning; proposes a robust cooperative positioning control algorithm based on cross-coupling error model, which realizes the synchronous convergence of single-machine positioning error and double-machine cooperative positioning error. A cooperative trajectory tracking control method for dual robots oriented to continuous tracking of dynamic targets is proposed, which improves the cooperative trajectory tracking accuracy of dual robots in continuous motion process and realizes visual servoing cooperative trajectory tracking of dual robots; a visual servoing cooperative processing system based on hierarchical structure is built to realize high-precision hole-making and milling by dual robots.

(1) The performance evaluation method of mobile robot integrated operation was studied. Performance evaluation indicators including dexterity and center of gravity stability were proposed, and the physical constraint conditions of joint space under the continuous acceleration layer continuous condition of mobile robot continuous motion process were analyzed. The layered motion planning of system speed layer constraints and dexterity performance constraints was carried out by using task priority method combined with the stiffness performance evaluation index of robots in the system’s continuous motion process. Simulation results showed that through the mobile robot integrated motion planning method based on task priority method, the stiffness performance planning results in the continuous operation process had been greatly improved compared with the case without stiffness constraints under the condition of satisfying the physical constraint conditions of joint speed layer.

(2) The generation and superposition principle of consistency error in cooperative motion of dual robots were investigated. A cross-coupling visual servoing robust control method was proposed. To address the random single-machine and double-machine consistency errors generated during the cooperative positioning process of dual robots, a cross-coupling consistency error model based on consideration of single-machine errors on both sides was established. A robust controller was designed for synchronous convergence of single-machine error and consistency error. Experimental results demonstrate that the cooperative control method can achieve a cooperative positioning accuracy of 0.15 mm.

(3) A dynamic visual servoing cooperative control method for dual robots was proposed to address the continuous trajectory tracking requirements in the cooperative operation process of dual robots. A third-order dual-target pose smoothing estimation algorithm was proposed to solve the problem of measurement noise in the high-speed motion trajectory tracking process of the end effector, laying a foundation for high-precision pose measurement and tracking of the end effector on both sides during continuous trajectory tracking. A cross-coupling robust control method for dual robots was proposed for continuous trajectory dynamic tracking, and experimental results showed that its cooperative trajectory tracking accuracy can reach 0.2 mm.

(4) Based on the cooperative control theory research foundation in multi-robot collaborative “in-situ processing” process, a large-scale visual servoing dual-robot cooperative control hole/milling processing system based on the “IPC+real-time industrial fieldbus” overall framework was built for large-scale scenes. Dual-robot cooperative processing experiments were carried out based on the above physical experimental platform, and it was verified that the dual-view visual-guided large-field dual-robot cooperative processing method can effectively improve the consistency of processing accuracy of associated installation brackets.

In summary, this thesis has conducted in-depth research on the difficult problems in multi-robot in-situ machining process from two aspects: mobile robot integrated operation motion control and binocular vision servoing collaborative control of two robots. At the theoretical level, it proposes a mobile robot integrated operation motion control method oriented to the optimal stiffness performance of the operation and a high-precision collaborative control method of binocular vision servoing based on cross-coupling error model for two robots. At the application level, based on the self-developed visual servoing two-robot collaborative machining system, it has completed the collaborative machining task of surface-related size support brackets of large and complex components simulation parts.

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