发现人类能力间的互补关系，用于优化人机任务分配与测试设计
Conjugated Capabilities: Interrelations of Elementary Human Capabilities and Their Implication on Human-Machine Task Allocation and Capability Testing Procedures
- 识别基础能力间的相互补偿机制，构建能力关联网络
- 基于康复患者数据验证能力间可动态转移努力以弥补短板
- 适用于制造场景中人机协作优化，提升测试效率与任务分配合理性
人类与自动化系统的能力是人机交互的基础。为实现有效协同，机器需理解人类能力表现并相应调整行为。本文提出“共轭能力”概念，即相互依赖、可分担努力的能力组合。例如，手臂伸展受限时，可通过前倾躯干来补偿。研究基于IMBA标准分析基础能力间的关联性，揭示潜在共轭关系，并在康复后患者数据中提供实证支持。以静态制造场景为例，构建了能力间互相关联的网络图谱。该图谱可用于优化IMBA测试流程，显著加快数据采集速度；同时探讨了共轭能力对人机任务分配的影响，为智能系统适应性设计提供新范式。
原文摘要 · Abstract (English)
Human and automation capabilities are the foundation of every human-autonomy interaction and interaction pattern. Therefore, machines need to understand the capacity and performance of human doing, and adapt their own behavior, accordingly. In this work, we address the concept of conjugated capabilities, i.e. capabilities that are dependent or interrelated and between which effort can be distributed. These may be used to overcome human limitations, by shifting effort from a deficient to a conjugated capability with performative resources. For example: A limited arm's reach may be compensated by tilting the torso forward. We analyze the interrelation between elementary capabilities within the IMBA standard to uncover potential conjugation, and show evidence in data of post-rehabilitation patients. From the conjugated capabilities, within the example application of stationary manufacturing, we create a network of interrelations. With this graph, a manifold of potential uses is enabled. We showcase the graph's usage in optimizing IMBA test design to accelerate data recordings, and discuss implications of conjugated capabilities on task allocation between the human and an autonomy.
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