NEWS ARTICLE
学术动态：Vision-Based Person-Following Algorithm for Assistive Elderly-Care Quadruped Robots
论文标题：Vision-Based Person-Following Algorithm for Assistive Elderly-Care Quadruped Robots
发布日期：2026-05-21
作者：Vishnudev Kurumbaparambil, Subashkumar Rajanayagam, Stefan Twieg
DOI：10.3390/s26103263
论文摘要：The demographic shift towards an aging population necessitates innovative solutions for care and mobility support. While commercial quadruped robots like the Unitree Go1 offer dynamic stability, their native following modes often lack the safety margins and predictability required, and they do not consistently follow the user, at times deviating and navigating independently. This paper presents a robust, vision-based, person-following algorithm designed to address these limitations. Utilizing a ZED 2 stereo camera and Robot Operating System (ROS), the system employs a finite state machine to ensure deterministic target tracking. A velocity control strategy partitions the robot’s motion into distinct stability, proportional, and braking zones based on depth data to ensure fluid interaction. The framework was validated on a Unitree Go1 quadruped platform in an outdoor environment involving 90-degree turns to evaluate tracking robustness. By operating in a headless mode, the system achieved a mean processing latency of 66.5±4.3 ms. Experimental results demonstrated consistent operational stability, 0.0% intrusion into the intimate safety zone, and effective velocity synchronization between 0.47 and 0.54 m/s. While this study establishes a robust technical baseline using healthy subjects, it serves as a preliminary development platform; further iterative testing with elderly users in clinical settings is required to move toward deployment. Beyond the evaluated trials, the framework maintained reliable functional performance across various care facility workshops, successfully following the target in all deployment scenarios. These findings establish a stable technical foundation for the future development of robotic walking partners.
元数据：Crossref 收录的 MDPI Sensors 论文。 DOI: 10.3390/s26103263. Vol. 26, Issue 10. Authors: Vishnudev Kurumbaparambil, Subashkumar Rajanayagam, Stefan Twieg.
开放许可：https://creativecommons.org/licenses/by/4.0/
原文链接：https://doi.org/10.3390/s26103263
PDF 链接：https://www.mdpi.com/1424-8220/26/10/3263/pdf