提出事件触发框架，提升人机协作中信任与效率的动态平衡。
An Event-Triggered Framework for Trust-Mediated Human-Autonomy Interaction
- 用事件触发机制捕捉人机交互的间歇性特征。
- 融合认知心理学与自主系统模型，建模人类对机器的信任变化。
- 在搜救机器人集群场景中验证参数调优策略的有效性。
受人类与自主系统协作日益增多的启发，我们提出一种新的混合系统框架，用于捕捉此类交互背后的相互关联动态。该框架整合了来自自主系统与认知心理学文献中的模型，以表征人类对自主系统的信任等关键要素。通过在人机接口处采用异步事件触发采样，框架引入了人类交互的间歇性特征。我们通过一个实际应用——自主机器人集群搜救任务，探讨了框架参数调优的重要考虑因素。结果表明，该框架有助于设计更高效、更有效的协同交互机制。
原文摘要 · Abstract (English)
Inspired by the increased cooperation between humans and autonomous systems, we present a new hybrid systems framework capturing the interconnected dynamics underlying these interactions. The framework accommodates models arising from both the autonomous systems and cognitive psychology literature in order to represent key elements such as human trust in the autonomous system. The intermittent nature of human interactions are incorporated by asynchronous event-triggered sampling at the framework's human-autonomous system interfaces. We illustrate important considerations for tuning framework parameters by investigating a practical application to an autonomous robotic swarm search and rescue scenario. In this way, we demonstrate how the proposed framework may assist in designing more efficient and effective interactions between humans and autonomous systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。