A Control-Theoretic Approach to Learning and Approximate Dynamic Programming (ADP) with Applications to High Performance Racing

学习和近似动态规划 (ADP) 的控制理论方法及其在高性能赛车中的应用

• 批准号: 0401405
• 负责人: Jennie Si
• 金额: $ 19万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2007-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0401405&HistoricalAwards=false
• 关键词: Control; Theoretic; Approach; Learning; Approximate

This project will use an autonomous racing vehicle as a testbed (and educational tool) for new types of intelligent system design. The project will focus on the challenge of blending concepts from computational intelligence (such as reinforcement learning) and control theory (such as hybrid control) so as to manage a complex system over multiple time scales, in an integrated way, adaptively, and with foresight. The goal in the testbed will simply be to minimize lap time - but it is hoped that the results will be useful to the development of unmanned autonomous vehicles (UAV) in general. A primary goal of the project is to build new partnerships across disciplines, as discussed in the NSF-supported workshop described at www.eas.asu.edu/~nsfadp, and to create a crossdisciplinary graduate course supporting these goals.

该项目将使用自动赛车作为新型智能系统设计的试验床(和教育工具)。该项目将侧重于将计算智能(如强化学习)和控制理论(如混合控制)的概念相结合的挑战，以便以综合的方式、适应性和前瞻性地在多个时间尺度上管理复杂的系统。试验台的目标只是最大限度地减少一圈的时间-但希望结果将有助于无人驾驶自动驾驶车辆(UAV)的总体发展。该项目的一个主要目标是建立跨学科的新伙伴关系，如www.eas.asu edu/~nsfadp上描述的NSF支持的研讨会所讨论的那样，并创建一个支持这些目标的跨学科研究生课程。