RI: Small: Collaborative Research: Why is Automating the Design of Robot Controllers Hard, and What Can Be Done About It

RI：小型：协作研究：为什么机器人控制器的自动化设计很难，以及可以采取什么措施

• 批准号: 1527436
• 负责人: Dylan Shell
• 金额: $ 22.5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527436&HistoricalAwards=false
• 关键词: RI; Small; Collaborative; Research; Why

This project seeks to bring together new techniques for filtering and planning to improve reasoning and analysis steps employed during robot design.By understanding those parts of the design process that are typically conducted by hand and by asking which parts can be practically automated, the research has the potential to assist practitioners by scaling up the problems tackled, optimizing systems automatically, and ultimately freeing designers from low-level detail and elevating their use of time.

这个项目寻求将过滤和规划的新技术结合在一起，以改进机器人设计过程中使用的推理和分析步骤。通过了解设计过程中通常由手工完成的部分，并通过询问哪些部分实际上可以实现自动化，该研究有可能通过扩大解决的问题、自动优化系统，最终将设计师从低层细节中解放出来，提高他们对时间的使用，从而帮助实践者。

项目成果

Cover Combinatorial Filters and Their Minimization Problem

涵盖组合滤波器及其最小化问题

• DOI: 10.1007/978-3-030-66723-8_6
• 发表时间: 2020
• 期刊: Workshop on the Algorithmic Foundations of Robotics
• 作者: Zhang, Yulin;Shell, Dylan A.
• 通讯作者: Shell, Dylan A.