NRI: INT: Balancing Collaboration and Autonomy for Multi-Robot Multi-Human Search and Rescue

NRI：INT：平衡多机器人多人搜索和救援的协作与自主

基本信息

批准号：
1830414
负责人：
Ryan Williams
金额：
$ 147.47万
依托单位：
Virginia Polytechnic Institute and State University
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：
2018-10-01 至 2023-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830414&HistoricalAwards=false
关键词：
NRI INT Balancing Collaboration Autonomy

项目摘要

Each year, thousands of people go missing in the United States. Coordinated search and rescue (SAR) operations provide the best chance to locate a missing individual alive. However, challenging terrain and other search constraints represent a barrier to human searchers. This project therefore seeks to enable collaboration between human searchers and unmanned aerial vehicles (UAVs) to improve searches while reducing human effort. Specifically, this project asks: How do we select and assign search tasks that ensure long-term human-robot collaboration, while deploying robots to complement human searchers in real-time? This project aims to answer this question through optimization, behavioral modeling, human-robot interaction, and computation, with evaluation in large-scale prototypes supported by the SAR community. Finally, impacts beyond SAR include: (1) education focused on co-robots; (2) theory for human-robot interaction in collaborative settings; (3) portable, low-cost, low-power computational infrastructure suitable for a wide range of applications; (4) technologies that foster economic opportunity around co-robots; and (5) field experiences for students from groups underrepresented in engineering.This project focuses on new theory and technologies for: (1) a minimally invasive, adaptive, multi-UAV control system leveraging risk-aware multi-robot planning for human-in-the-loop (HITL) control; (2) distributed computing that opportunistically exploits and balances multi-robot interaction, communication, computation, and decision-making; and (3) an interface between human searchers and UAVs that allows control from complete autonomy to manual operation, including testable interfaces for exploration vs. exploitation strategies. This project addresses fundamental challenges critical to the scalability of multi-robot multi-human teams: (1) planning and control systems for UAVs that can autonomously gather information in a cooperative and distributed way while adapting to uncertain human plans; (2) interfaces for human-robot interactions that allows collaboration that appropriately balances exploration with exploitation; and (3) real-time support to analyze, store, and share data subject to the power and connectivity constraints typical of real-world deployments.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.

每年，美国成千上万的人失踪。协调的搜救（SAR）操作为找到一个失踪的人活着提供了最佳机会。但是，具有挑战性的地形和其他搜索约束代表了人类搜索者的障碍。因此，该项目旨在使人类搜索者和无人机（UAV）之间的合作能够改善搜索，同时减少人类努力。具体来说，该项目询问：我们如何选择并分配确保长期人类机器人协作的搜索任务，同时部署机器人实时补充人类搜索者？该项目旨在通过优化，行为建模，人类机器人互动和计算来回答这个问题，并在SAR社区支持的大规模原型中进行评估。最后，超越SAR的影响包括：（1）专注于共同机器人的教育；（2）协作环境中人类机器人互动的理论；（3）适用于广泛应用的便携式，低成本，低功率计算基础架构；（4）围绕共同机器人促进经济机会的技术；（5）工程中代表性不足的学生的现场经验。本项目重点介绍：（1）以下新的理论和技术，一种微创，适应性，多UAV控制系统利用了风险意识的多机器人计划，用于人类在卢布（HITL）控制；（2）分布式计算，可以机会利用和平衡多机器人交互，通信，计算和决策；（3）人类搜索者与无人机之间的接口允许从完整的自主权到手动操作的控制，包括可测试的探索接口与剥削策略。该项目解决了对多机器人多人类团队的可伸缩性至关重要的基本挑战：（1）无人机的计划和控制系统可以自主地以合作和分布式方式自主收集信息，同时适应不确定的人类计划；（2）人类机器人相互作用的界面，可以合适地平衡探索与剥削的协作；（3）实时支持，以分析，存储和共享数据，但按照现实世界部署的权力和连接限制的约束。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的评估标准通过评估来获得支持的。