基于运动控制器的实验系统功能开发

Functional Development of an Experimental System Based on a Motion Controller

摘要: 针对当前机器人学教学中实验设备封闭、核心算法不透明的痛点，本文设计并实现了一套基于运动控制器的开放式教学实验系统。系统采用上下位机协同架构，以雷赛BAC632E运动控制器为核心，通过EtherCAT总线连接SCARA与Delta机械臂，构建了实时控制网络。研究的核心创新在于将机器人运动学算法从上位机“下移”至控制器内核，通过算法重构与自定义函数库开发，克服了控制器BASIC语言的环境限制。实验结果表明，下移后的几何解析法计算效率较上位机雅可比数值法提升约4.3倍，且稳定性更优。本文还设计了多层次教学实验，验证了该系统在帮助学生直观理解D-H参数、运动学算法等方面的有效性与教学价值，为机器人实践教学提供了理想的开放平台。

Abstract: Aiming at the pain points of closed experimental equipment and opaque core algorithms in current robotics teaching, this paper designs and implements an open teaching experimental system based on a motion controller. The system adopts a master-slave computer cooperative architecture, with the LBC BAC632E motion controller as the core, and connects SCARA and Delta manipulators via EtherCAT to form a real-time control network. The core innovation of the research lies in the “migration” of the robot kinematics algorithm from the host computer to the controller kernel. Through algorithm refactoring and the development of custom function libraries, the limitations of the controller’s BASIC language environment were overcome. Experimental results show that the migrated geometric analytical method achieves a computational efficiency approximately 4.3 times higher than the Jacobian numerical method running on the host computer, with better stability. This paper also designs multi-level teaching experiments, verifying the system’s effectiveness and teaching value in helping students intuitively understand D-H parameters and kinematics algorithms, providing an ideal open platform for robotics practical education.