统一机器人和惯性传感器自我校准
James M Ferguson1, Tayfun Efe Ertop1, S Duke Herrell2
1Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, USA.
Robotica
|September 21, 2023
概括
本研究介绍了一种快速,廉价的方法,可以同时校准机器人和惯性测量单元 (IMU). 通过将IMU连接到机器人并将其移动,两种系统都可以在没有外部设备的情况下进行校准.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 传感器融合式传感器
- 校准技术 校准技术
背景情况:
- 机器人和惯性测量单元 (IMU) 的独立校准是昂贵的,需要专门的设备,如自动化测试平台和高精度跟踪系统.
- 目前的方法需要对机器人和IMU进行单独的校准过程,增加时间和费用.
- 现有的方法通常依赖于昂贵的外部测量系统来准确确定姿势.
研究的目的:
- 为机器人和IMU的同时校准提供一种新,成本效益高,精简的方法.
- 消除对昂贵的外部追踪系统和专用测试装置的需求.
- 通过简单地将IMU连接到机器人的端效应器并执行连续运动来实现校准.
主要方法:
- 使用连续时间批量估计,以获得统计学上最佳的解决方案.
- 根据高斯的假设,将校准表达为非线性最小平方问题.
- 分析与估计问题相关的雅可比矩阵结构.
主要成果:
- 展示了同时使用IMU和机器人运动进行机器人和IMU校准的方法.
- 在没有外部测量系统的情况下实现校准,降低成本和复杂性.
- 通过数值模拟和实验测试进行验证,显示与传统方法相比或优于传统方法的结果.
结论:
- 拟议的方法提供了一个快速,简单和廉价的替代方案,用于同时校准机器人和IMU.
- 连续时间批量估计为同时进行传感器和机器人校准提供了高效和准确的解决方案.
- 这种方法显著降低了各种应用中精确的机器人和IMU校准的进入壁垒.
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