Real-Time Surface Identification System for Variable Walking Speeds of Biped Robots
Real-Time Surface Identification System for Variable Walking Speeds of Biped Robots
复制标题
双足机器人变速行走的实时表面识别系统
DOI：
10.1109/les.2023.3299114
复制
发表时间：
2024
影响因子：
1.6
通讯作者：
H. Mattausch
中科院分区：
文献类型：
--
作者：
Aiwen Luo;S. Bhattacharya;M. Miura;Yicong Zhou;H. Mattausch
识别机器人运动过程中不同速度下的下垫面对于机器人安全有效的导航是非常重要的。这项工作的目的是提高感知能力的机器人，使每只脚下面的力传感器，以识别多个室内表面，同时以不同的速度导航。提出了一种精确而经济的机器人表面识别系统，结合实时多目标支持向量机（SVM）与有效的时域特征。在这种情况下，四个有前途的手工制作的时域功能进行了研究，其中的均方根（RMS）功能被证明优于其他三个功能。在两种不同的步行速度下应用RMS，十倍SVM交叉验证的平均精度（mAP）分别为95.99%和98.16%。高分类精度是通过高计算效率实现的，因此可以在低成本平台（如Arduino或Jetson Nano）上部署系统，这使得我们的方法适用于各种步行速度的广泛应用。
Identifying the underlying surface at varying speeds during robotic locomotion is important for safe and efficient robot navigation. This work aims to enhance the perceptual abilities of biped robots by enabling the force sensor affixed beneath each foot to recognize multiple indoor surfaces while navigating at varying speeds. An accurate yet cost-efficient surface-identification system for the robot is proposed by combining a real-time multiobject support vector machine (SVM) with an efficient time-domain feature. In this context, four promising hand-crafted time-domain features are investigated, among which the root mean square (RMS) feature is proven to outperform the other three features. A mean average precision (mAP) of 95.99% and 98.16% in tenfold SVM cross-validation can be achieved by applying RMS at two different walking speeds, respectively. The high classification accuracy is achieved with high computing efficiency and thus enables system deployment on low-cost platforms, such as Arduino or Jetson Nano, which makes our approach suitable for a wide range of applications across varying walking speeds.