Towards Modeling & Simulation-Enabled Design of Intelligent Robots A Meeting Dedicated to Identifying Opportunities, Summarizing Challenges, and Brainstorming for Impactful Di

迈向建模

• 批准号: 1830129
• 负责人: Dan Negrut
• 金额: $ 2.99万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830129&HistoricalAwards=false
• 关键词: Towards; Modeling; & Simulation; Enabled

Robots are becoming increasingly expected to operate in complex, unstructured environments. To successfully achieve their tasks, they must use models to plan and control their actions. For reliable performance, these models should adequately capture the types of interactions the robot has with the world.This workshop brings together researchers in the areas of robotics, modeling and simulation (M&S), and machine learning (ML), to examine the roles that M&S and ML play in robotic planning and control, and how these two different approaches can be combined to produce robust robot behavior. Approximately 35 researchers from academia and industry, from various backgrounds, are invited to participate in open discussion and brainstorming sessions. The one-day format, held at the National Institute of Standards and Technology (NIST), includes overview talks and breakout sessions. The outcome will be a report summarizing the main ideas and themes that emerge from the discussions, with the aim of publishing the results in a robotics journal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人们越来越期望机器人能够在复杂、非结构化的环境中运行。 为了成功完成任务，他们必须使用模型来计划和控制他们的行动。 为了获得可靠的性能，这些模型应充分捕捉机器人与世界的交互类型。本次研讨会汇集了机器人、建模与仿真 (M&S) 以及机器学习 (ML) 领域的研究人员，以研究机器人所扮演的角色M&S 和 ML 在机器人规划和控制中发挥作用，以及如何结合这两种不同的方法来产生稳健的机器人行为。大约 35 名来自学术界和工业界、不同背景的研究人员受邀参加公开讨论和头脑风暴会议。 为期一天的活动在美国国家标准与技术研究所 (NIST) 举行，包括概述讲座和分组会议。 结果将是一份总结讨论中出现的主要想法和主题的报告，旨在在机器人学期刊上发表结果。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。