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A novel tracking system for human following robots with fusion of MMW radar and monocular vision
Industrial Robot ( IF 1.8 ) Pub Date : 2021-09-16 , DOI: 10.1108/ir-02-2021-0030
Yipeng Zhu 1 , Tao Wang 1 , Shiqiang Zhu 2
Affiliation  

Purpose

This paper aims to develop a robust person tracking method for human following robots. The tracking system adopts the multimodal fusion results of millimeter wave (MMW) radars and monocular cameras for perception. A prototype of human following robot is developed and evaluated by using the proposed tracking system.

Design/methodology/approach

Limited by angular resolution, point clouds from MMW radars are too sparse to form features for human detection. Monocular cameras can provide semantic information for objects in view, but cannot provide spatial locations. Considering the complementarity of the two sensors, a sensor fusion algorithm based on multimodal data combination is proposed to identify and localize the target person under challenging conditions. In addition, a closed-loop controller is designed for the robot to follow the target person with expected distance.

Findings

A series of experiments under different circumstances are carried out to validate the fusion-based tracking method. Experimental results show that the average tracking errors are around 0.1 m. It is also found that the robot can handle different situations and overcome short-term interference, continually track and follow the target person.

Originality/value

This paper proposed a robust tracking system with the fusion of MMW radars and cameras. Interference such as occlusion and overlapping are well handled with the help of the velocity information from the radars. Compared to other state-of-the-art plans, the sensor fusion method is cost-effective and requires no additional tags with people. Its stable performance shows good application prospects in human following robots.



中文翻译:

一种新型毫米波雷达与单目视觉融合的跟随机器人跟踪系统

目的

本文旨在为人类跟随机器人开发一种鲁棒的人员跟踪方法。跟踪系统采用毫米波(MMW)雷达和单目摄像头的多模态融合结果进行感知。使用所提出的跟踪系统开发和评估了人类跟随机器人的原型。

设计/方法/方法

受角分辨率的限制,来自毫米波雷达的点云太稀疏而无法形成用于人体检测的特征。单目相机可以为视野中的物体提供语义信息,但不能提供空间位置。考虑到两种传感器的互补性,提出了一种基于多模态数据组合的传感器融合算法,以在具有挑战性的条件下识别和定位目标人。此外,还设计了一个闭环控制器,让机器人以预期的距离跟随目标人。

发现

进行了一系列不同情况下的实验来验证基于融合的跟踪方法。实验结果表明,平均跟踪误差在0.1 m左右。还发现机器人可以处理不同的情况并克服短期干扰,持续跟踪和跟随目标人。

原创性/价值

本文提出了一种融合毫米波雷达和相机的鲁棒跟踪系统。借助来自雷达的速度信息,可以很好地处理遮挡和重叠等干扰。与其他最先进的计划相比,传感器融合方法具有成本效益,并且不需要额外的人员标签。其稳定的性能在人跟随机器人中显示出良好的应用前景。

更新日期:2021-09-16
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