Analyzing and Modeling Human Adaptive Spatial Control Skills Using General Principles of Optimal Control

使用最优控制的一般原理对人类自适应空间控制技能进行分析和建模

• 批准号: 1002298
• 负责人: Berenice Mettler
• 金额: $ 27万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1002298&HistoricalAwards=false
• 关键词: Analyzing; Modeling; Human; Adaptive; Spatial

The research objective of this award is to reverse-engineer human spatial control skills, with the goal of bridging the gap between human and autonomous systems. Adaptive and versatile spatial control capabilities are essential to successfully deploying unmanned aerial vehicles and other applications of autonomous control. understanding how humans achieve these skills is also important for the design of man-machine systems, such as active safety systems for helicopters or even tele-surgery systems. The research approach combines psycho-behavioral experiments and the application of control-theoretic principles. The working hypothesis is that human spatial behavior is determined by combining a type of model predictive control (MPC) process and a spatial value function (SVF). The MPC process describes how a trajectory is generated online,based on the immediate sensed environment; the SVF describes how the global environment and task elements are encoded and used in the MPC process. This model will then be used to study how the pilot adapts his/her strategies in the presence of disturbances, environment ncertainties, or when presented with novel ituations. Deliverables include the details of the odeling framework, documentation of research results, and outcomes of interdisciplinary student education and research experience.If successful, this research will lead to developing new algorithms to model and replicate human daptability in spatial control tasks, paving the way for novel technologies for autonomous vehicle ontrol with unprecedented performance and adaptability. The improved understanding of human uidance skills will provide a gateway to new operator interfaces, augmenting human unctionality, effectiveness, and safety. Furthermore, the modeling framework will providefoundations for neurological studies, aimed at understanding the brain?s implementation of the patial control processes. Finally, the proposed interdisciplinary research activities will promote ew teaching and outreach activities, while attracting students from diverse backgrounds.

该奖项的研究目标是对人类空间控制技能进行反向工程，目的是弥合人类和自主系统之间的差距。自适应和多功能的空间控制能力是成功部署无人机和其他自主控制应用的关键。了解人类如何获得这些技能对于人机系统的设计也很重要，例如直升机的主动安全系统，甚至远程手术系统。研究方法结合了心理行为实验和控制论原理的应用。工作假设是，人类的空间行为是由一种模型预测控制(MPC)过程和一种空间价值函数(SVF)相结合来确定的。MPC流程描述了如何基于直接感知的环境在线生成弹道；SVF描述了全局环境和任务元素如何在MPC流程中编码和使用。然后，这个模型将被用来研究飞行员在存在干扰、环境不确定性或面临新的飞行时如何适应他/她的策略。成果包括建模框架的细节，研究结果的文档，以及跨学科学生教育和研究经验的结果。如果成功，这项研究将导致开发新的算法来模拟和复制人类在空间控制任务中的适应性，为具有前所未有的性能和适应性的自动车辆控制的新技术铺平道路。对人类引导技能的更好理解将提供通往新操作员界面的门户，增强人类的功能性、有效性和安全性。此外，该建模框架将为神经学研究提供基础，旨在了解大脑-S实施的空间控制过程。最后，拟议的跨学科研究活动将促进新的教学和外联活动，同时吸引来自不同背景的学生。