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从复杂性到商业准备:关于弥合人机交互和社交机器人导航差距的行业见解

Lina Moe¹, Benjamin Greenberg²

¹Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ, United States.

Frontiers in robotics and AI

|January 1, 2026

概括

行业专业人士面临的挑战是将社会移动机器人整合到人类环境中. 不同的人类检测方法和工业-学术界差距影响机器人开发和社会导航.

科学领域:

机器人技术机器人技术机器人技术
人与机器人的交互
人工智能的人工智能

背景情况:

将移动机器人集成到人类环境中,给机器人学家带来了重大挑战.
社交移动机器人需要先进的功能,以实现安全有效的人类互动.

研究的目的:

调查行业在社交移动机器人技术中对人体检测和代表性的方法.
探索行业与学术界关系对研发过程的影响.

主要方法:

定性研究涉及采访十六个行业专业人士在社会移动机器人.
对人体检测,系统设计和成功指标的方法分析.

主要成果:

采用了各种各样的人类检测策略,从基本的避难障碍到复杂的人类分类.
机器人系统设计和人类检测受安全与社交框架,系统复杂性和成功指标的影响.
学术研究和行业需求之间存在差距和协同作用,特别是在商业准备和HRI集成方面.

结论:

解决社会导航的复杂性对于现实世界的机器人部署至关重要.
工业和学术界之间的加强沟通可以促进机器人的发展,以实现物理和社会整合.

关键词:

产业产业产业产业产业产业面试面试面试面试面试移动机器人移动机器人导航导航导航导航导航人类检测,人身检测.定性研究是指质量研究.

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