基于大数据聚类的工业遥操作机器人位姿定位控制系统设计

针对工业遥操作机器人位姿定位过程中难以同步控制位置和姿态角，导致位姿定位准确性较差的问题，利用大数据聚类技术，从硬件和软件两个方面优化设计工业遥操作机器人位姿定位控制系统。通过位姿传感器的改装，保证传感器设备能够同时测量机器人位置与姿态，改装定位控制器和驱动器。在系统硬件的支持下，考虑机器人组成结构、运动原理和动力学理论，构建机器人数学模型，在该模型下模拟机器人遥操作过程，确定机器人位姿的定位控制目标。实时采集机器人位姿数据，利用大数据聚类技术计算定位控制量，在控制器的约束下，实现系统的位姿定位控制功能。通过系统测试实验得出结论：综合多种类型的运动情况，在优化设计系统的控制下，机器人的位置误差平均值为4.5mm，姿态角控制误差为0.04°。

Design of position and orientation control system for industrial teleoperation robot based on big data clustering

Aiming at the problem that it is difficult to control the position and attitude angle synchronously in the position and orientation positioning process of industrial teleoperation robot, which leads to the poor accuracy of position and orientation positioning, the position and orientation positioning control system of industrial teleoperation robot is optimized and designed from both hardware and software by using big data clustering technology. Through the modification of the position and attitude sensor, it is ensured that the sensor equipment can measure the position and attitude of the robot at the same time, and the positioning controller and driver are modified. With the support of the system hardware, considering the composition and structure of the robot, the principle of motion and the theory of dynamics, the mathematical model of the robot is constructed. Under this model, the teleoperation process of the robot is simulated, and the positioning control target of the robot''s posture is determined. Real-time collection of robot pose data, use of big data clustering technology to calculate the positioning control amount, under the constraints of the controller, realize the positioning control function of the system. Through the system test experiment, it is concluded that under the control of the optimized design system, the average position error of the robot is 4.5 mm and the attitude angle control error is 0.04 °.