基于速度命令执行的四轮差分机器人两种系统识别方法的比较
Diego Guffanti1, Moisés Filiberto Mora Murillo2,3, Marco Alejandro Hinojosa4
1Universidad UTE, Av. Mariscal Sucre, Quito 170129, Ecuador.
Sensors (Basel, Switzerland)
|September 19, 2025
概括
基于电机的模型 (MBM) 与简化模型 (SM) 相比,在微分驱动机器人测距方面提供了更高的精度. 然而,SM提供了更快的计算,使模型选择对自主导航任务至关重要.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 自主导航自主导航自主导航自主导航自主导航自主导航
背景情况:
- 差速驱动机器人的精确建模对于自动驾驶系统至关重要.
- 两种不同的建模方法,即基于电机的模型 (MBM) 和简化的模型 (SM),被评估为四轮差速驱动机器人.
研究的目的:
- 为了比较分析MBM和SM的准确性和计算性能,用于微分驱动机器人建模.
- 评估模型选择对测距精度和导航任务设计的影响.
主要方法:
- MBM使用四个电机特定的传输函数,而SM使用两种传输函数用于线性和角速度.
- 这两种模型都与差异驱动机器人上的SLAM系统的真实测距数据进行了验证.
主要成果:
- 与SM相比,MBM在位置和方向估计方面表现出更高的准确性,RMSE值较低.
- SM表现出卓越的计算性能,实现了对模拟时间的30%的减少和更低的内存使用量.
- MBM显示SM的平均位置RMSE为0.309m与0.414m;SM的角RMSE为0.170rad与0.239rad.
结论:
- MBM更适合要求高精度的应用,例如SLAM.
- 对于资源受限的嵌入式系统,需要更快的计算,SM是有利的.
- 模型复杂性,准确性和计算成本之间的权衡对于选择合适的机器人模型至关重要.
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