REU Site: Applied Computational Robotics

REU 网站：应用计算机器人

• 批准号: 2313928
• 负责人: Jason O'Kane
• 金额: $ 40.5万
• 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: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313928&HistoricalAwards=false
• 关键词: REU; Site; Applied; Computational; Robotics

This Research Experiences for Undergraduates (REU) Site will support a diverse group of 10 undergraduate students in a 10-week mentored research experience in computational robotics, including components emphasizing professional and academic skills development and community building. The primary population of target students will be sophomores and juniors from undergraduate-serving institutions in the southeast. The project will encourage these students toward graduate study and research-oriented industry positions in robotics and related areas of computing, and provide essential preparation for these career paths. It will be an excellent opportunity for undergraduates to participate in research projects each year. The emphasis on applications of computing in robotics is supportive of the growing social need for such expertise. The selection process for these students will promote the inclusion of underrepresented groups through targeted publicity and outreach efforts. Research conducted by the students will lead to more effective approaches to robot perception, control, and learning. The research spans projects rooted in areas are often overlooked by the contemporary robotics community, but crucially important for the deployment of reliable, trustworthy robotic systems. Participants will engage in scientifically-relevant research projects organized around the observation that "Robots Change Everything." That is, when computers are utilized to enable autonomy in robotic systems, the complexity and unpredictability of the physical world have profound implications on nearly every aspect of that computing system, from the application-specific algorithms and data structures, all the way down to the lower-level considerations of security and network connectivity.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.

这项针对本科生（REU）网站的研究经验将在10周的计算机器人技术方面为10周的指导研究经验提供支持，其中包括强调专业和学术技能发展和社区建设的组件。目标学生的小学人群将是东南部本科生的大二学生和大三学生。该项目将鼓励这些学生在机器人技术和相关领域的研究生学习和以研究为导向的行业职位，并为这些职业道路提供必要的准备。这将是本科生每年参加研究项目的绝佳机会。对计算在机器人技术中的应用的重视是支持对这种专业知识的社会需求的增长。这些学生的选择过程将通过有针对性的宣传和推广工作来促进代表性不足的群体。 学生进行的研究将导致更有效的机器人感知，控制和学习的方法。 当代机器人社区通常会忽略植根于地区的研究，但对于部署可靠，值得信赖的机器人系统至关重要。 参与者将围绕“机器人改变一切”的观察组织进行与科学相关的研究项目。也就是说，当计算机被用来在机器人系统中启用自主权时，物理世界的复杂性和不可预测性对计算系统的几乎每个方面都具有深远的影响，从特定于应用程序的算法和数据结构一直到质量。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来表示支持的。

项目成果

Closed-Loop Control of Magnetic Modular Cubes for 2D Self-Assembly

用于二维自组装的磁性模块化立方体的闭环控制

• DOI: 10.1109/lra.2023.3296008
• 发表时间: 2023
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Lu, Yitong;Bhattacharjee, Anuruddha;Taylor, Conlan C.;Leclerc, Julien;O'Kane, Jason M.;Kim, MinJun;Becker, Aaron T.
• 通讯作者: Becker, Aaron T.

Confined Water Body Coverage under Resource Constraints

资源约束下的承压水体覆盖范围

• DOI: 10.1109/iros47612.2022.9981764
• 发表时间: 2022
• 期刊: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
• 作者: Salman, Ibrahim;Raiti, Jason;Karapetyan, Nare;Venkatachari, Archana;Bourbonnais, Annie;O'Kane, Jason M.;Rekleitis, Ioannis
• 通讯作者: Rekleitis, Ioannis