具身智能跟随移动机器人研究与进展
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1.中国科学院海西研究院泉州装备制造研究中心泉州362216; 2.福建省特种设备检验研究院福州350008; 3.福建(泉州)先进制造技术研究院泉州362000

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TH242 TH39

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福建省科技重大专项(2024HZ025022)、福建省特种智能装备安全与测控重点实验室开放基金项目(FJIES2023KF02)资助


Research and advances in embodied intelligent human-following mobile robots
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1.Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362216, China; 2.Fujian Special Equipment Inspection and Research Institute, Fuzhou 350008, China; 3.Fujian (Quanzhou) Institute of Advanced Manufacturing Technology, Quanzhou 362000, China

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    摘要:

    具身智能跟随移动机器人是一种能够识别、跟踪并协同人类目标移动的智能系统,其发展已从“功能化工具”逐步演进为“情境化智能体”,标志着从“机器人在环境中运行”到“机器人通过身体理解环境并行动”的范式转变。基于“环境-身体-智能”的具身智能框架,系统梳理了跟随移动机器人的研究进展与发展趋势。首先,阐述具身智能的研究背景与目标,并论述其以环境交互、身体体验与智能涌现为核心的科学内涵。其次,梳理跟随移动机器人的技术演进、典型应用场景与产业趋势。通过深入分析机器人在多模态传感器、计算与处理单元、运动执行机构等方面的关键技术,进一步探讨其在仓储物流、公共交通、养老康复等典型场景的应用需求。然后,重点探讨自然高效的人机交互机制与协同策略。涵盖基于显式指令、隐式状态、物理接触和社交情感的人机交互方式,以及基于强化学习、模仿学习和迁移学习的人机交互策略,旨在提升机器人在社交环境中运行的流畅性与社会接纳度。最后,总结当前跟随移动机器人在环境深度认知、身体动态适配与智能持续演进等方面的主要技术挑战,并对算法泛化性、场景适应性与长期自主学习能力等未来发展方向进行展望。

    Abstract:

    Embodied intelligent human-following mobile robots are intelligent systems capable of recognizing, tracking, and coordinating their movement with human targets. They have gradually evolved from "functional tools" to "context-aware intelligent agents", marking a paradigm shift from "operating in the environment" to "understanding and acting in the environment through their bodies". Based on the embodied intelligence framework of "environment-body-intelligence", this paper systematically reviews the research progress and development trends of human-following mobile robots. First, it elaborates on the research background and objectives of embodied intelligence, discussing its scientific essence centered on environmental interaction, bodily experience, and emergent intelligence. Second, it outlines the technological evolution, typical application scenarios, and industrial trends. By conducting an in-depth analysis of key technologies such as multimodal sensors, computing and processing units, and motion execution mechanisms, the paper further explores the application requirements in typical scenarios such as warehousing and logistics, public transportation, and elderly care and rehabilitation. Next, it focuses on natural and efficient human-robot interaction mechanisms and collaborative strategies, which include human-robot interaction methods based on explicit commands, implicit states, physical contact, and social-emotional cues, as well as interaction strategies based on reinforcement learning, imitation learning, and transfer learning, all aimed at enhancing the robots′ operational fluency and social acceptance in social environments. Finally, the paper summarizes the main technical challenges in areas such as deep environmental cognition, dynamic bodily adaptation, and continuous intelligent evolution, and provides an outlook on future development directions.

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姚瀚晨,戴厚德,张思龙,郑耿峰,梁培栋.具身智能跟随移动机器人研究与进展[J].仪器仪表学报,2026,47(5):3-22

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  • 在线发布日期: 2026-07-24
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