分析智能机器人发展中的以人为本设计，揭示人机协同关键路径。
Human-Centered AI and Autonomy in Robotics: Insights from a Bibliometric Study
- 用文献计量法梳理人机共融机器人研究趋势与核心议题。
- 发现人工智能使机器人具备自适应行为，提升协作可靠性。
- 适合关注人机交互、智能系统设计的研究者和工程师参考。
自主机器人系统的发展为高精度、高一致性完成复杂任务提供了巨大潜力。近年来人工智能的进步推动了更强大的智能自动化系统，应对日益复杂的挑战。然而，这一进展也引发关于人类在系统中角色的思考。以人为本的人工智能（HCAI）旨在平衡人类控制与自动化，确保性能提升的同时保留创造力、掌控力与责任性。在实际应用中，自主机器人需兼顾任务表现、可靠性、安全性与可信度。融入HCAI原则可增强人机协作并保障负责任运行。本文基于Scopus数据库，采用SciMAT与VOSViewer进行文献计量分析，揭示学术趋势、新兴主题及人工智能在机器人自适应行为中的作用，重点聚焦HCAI架构。研究结果被映射至IBM MAPE-K架构，以探索如何将这些发现应用于真实场景下的自主机器人系统开发。
原文摘要 · Abstract (English)
The development of autonomous robotic systems offers significant potential for performing complex tasks with precision and consistency. Recent advances in Artificial Intelligence (AI) have enabled more capable intelligent automation systems, addressing increasingly complex challenges. However, this progress raises questions about human roles in such systems. Human-Centered AI (HCAI) aims to balance human control and automation, ensuring performance enhancement while maintaining creativity, mastery, and responsibility. For real-world applications, autonomous robots must balance task performance with reliability, safety, and trustworthiness. Integrating HCAI principles enhances human-robot collaboration and ensures responsible operation. This paper presents a bibliometric analysis of intelligent autonomous robotic systems, utilizing SciMAT and VOSViewer to examine data from the Scopus database. The findings highlight academic trends, emerging topics, and AI's role in self-adaptive robotic behaviour, with an emphasis on HCAI architecture. These insights are then projected onto the IBM MAPE-K architecture, with the goal of identifying how these research results map into actual robotic autonomous systems development efforts for real-world scenarios.
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