分析机器人在复杂环境中决策困境，提出人机协作优化方案。
The Dilemma of Decision-Making in the Real World: When Robots Struggle to Make Choices Due to Situational Constraints
- 通过情景分析法识别环境与用户不确定性带来的决策挑战。
- 发现个性化协作能显著提升残障人士在真实场景中的使用体验。
- 适合关注无障碍设计与人机协同的科研及产品团队参考。
为揭示助人机器人在嘈杂真实环境中的能力局限，本文提出一种决策情景分析方法，系统考察用户与环境不确定性带来的挑战，并融入用户研究。情景分析聚焦视觉、身体、认知、听觉障碍者及临床需求，结合噪声、光照、杂乱等环境因素，以及日常生活活动，强调通过增强人机协作实现个性化服务。本研究旨在推动机器人形态、传感、执行与认知能力的改进，提出一种突破性策略，以应对不确定条件下的决策难题。通过强调以用户为中心的设计原则，提供可落地的解决方案，帮助识别关键决策瓶颈并提出优化路径。
原文摘要 · Abstract (English)
In order to demonstrate the limitations of assistive robotic capabilities in noisy real-world environments, we propose a Decision-Making Scenario analysis approach that examines the challenges due to user and environmental uncertainty, and incorporates these into user studies. The scenarios highlight how personalization can be achieved through more human-robot collaboration, particularly in relation to individuals with visual, physical, cognitive, auditory impairments, clinical needs, environmental factors (noise, light levels, clutter), and daily living activities. Our goal is for this contribution to prompt reflection and aid in the design of improved robots (embodiment, sensors, actuation, cognition) and their behavior, and we aim to introduces a groundbreaking strategy to enhance human-robot collaboration, addressing the complexities of decision-making under uncertainty through a Scenario analysis approach. By emphasizing user-centered design principles and offering actionable solutions to real-world challenges, this work aims to identify key decision-making challenges and propose potential solutions.
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