开源工具箱，用实测数据精准预测机械臂能耗
EcBot: Data-Driven Energy Consumption Open-Source MATLAB Library for Manipulators
- 基于实测数据和机器人参数自动构建能耗模型
- 在4款轻型机械臂上测试，误差仅1.42~5.25W
- 适合机器人能效优化与绿色制造研究者使用
现有文献虽提出机械臂电耗估算模型，但普遍存在两大局限：一是多在传统工业机器人上验证，二是精度不足。为此，本文推出一个基于MATLAB的开源库，可自动为机械臂生成能耗（EC）模型。输入包括D-H参数、连杆质量与质心信息，以及实际运行数据（关节位置、速度、加速度、电耗及时间戳）。我们在三家厂商的四款轻型机器人（Universal Robots、Franka Emika、Kinova）上验证该方法。训练集上RMSE为1.42~2.80 W，测试集上为1.45~5.25 W，结果表明模型具备高精度与良好泛化能力。
原文摘要 · Abstract (English)
Existing literature proposes models for estimating the electrical power of manipulators, yet two primary limitations prevail. First, most models are predominantly tested using traditional industrial robots. Second, these models often lack accuracy. To address these issues, we introduce an open source Matlab-based library designed to automatically generate \ac{ec} models for manipulators. The necessary inputs for the library are Denavit-Hartenberg parameters, link masses, and centers of mass. Additionally, our model is data-driven and requires real operational data, including joint positions, velocities, accelerations, electrical power, and corresponding timestamps. We validated our methodology by testing on four lightweight robots sourced from three distinct manufacturers: Universal Robots, Franka Emika, and Kinova. The model underwent testing, and the results demonstrated an RMSE ranging from 1.42 W to 2.80 W for the training dataset and from 1.45 W to 5.25 W for the testing dataset.
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