迈向可靠的水下潜水员-机器人交互：手势设计、交互逻辑与真实世界评估
Towards Reliable Underwater Diver-Robot Interaction: Gesture Design, Interaction Logic, and Real-World Evaluation
- University of Science and Technology of China（中国科学技术大学）
- Institute of Artificial Intelligence (TeleAI), China Telecom（中国电信人工智能研究院（TeleAI））
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究通过闭环框架集成七手势词汇、关键点识别和命令级逻辑，经用户研究与水下实验验证，提升了水下人机交互的可靠性与执行稳定性。
AI中文摘要：
水下人机交互需要既易于潜水员使用又可靠地被机器人识别的手势命令。我们通过一个闭环的潜水员-机器人交互框架来研究这些方面，该框架集成了紧凑的七手势词汇表、轻量级的基于关键点的识别以及命令级交互逻辑。我们通过用户研究和在实验室水池及游泳池中进行的水下机器人实验来评估该框架。用户研究支持了在短暂学习后手势的可复现性。识别分析进一步表明，视觉相似性与手势混淆相关，而手势形成过程中的中间姿态引入了时间上的模糊性。命令级处理减轻了瞬时识别错误对机器人执行的影响，减少了意外触发和过早的任务中断。这些发现表明，可靠的水下手势交互依赖于水下交互中的人类可用性、手势可识别性和执行可靠性。
英文摘要：
Underwater human--robot interaction requires gesture commands that are both easy for divers to use and reliable for robots to recognize. We investigate these aspects through a closed-loop diver--robot interaction framework integrating a compact seven-gesture vocabulary, lightweight landmark-based recognition, and command-level interaction logic. We evaluate the framework through a user study and underwater robot experiments in a laboratory tank and a swimming pool. The user study supported the reproducibility of the gestures after brief learning. Recognition analysis further showed that visual similarity was associated with gesture confusion, while intermediate poses during gesture formation introduced temporal ambiguity. Command-level processing mitigated the effects of transient recognition errors on robot execution, reducing unintended triggers and premature task interruptions. These findings show that reliable underwater gesture interaction depends on human usability, gesture recognizability, and execution reliability in underwater interaction.
