NRI: Small: Multirobot-Human Coordination for Visual Scene Understanding

NRI：小型：用于视觉场景理解的多机器人与人类协调

• 批准号: 1316934
• 负责人: Amit Roy-Chowdhury
• 金额: $ 77.19万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1316934&HistoricalAwards=false
• 关键词: NRI; Small; Multirobot; Human; Coordination

The objective of this research is to enable the development of teams of robots, equipped with vision and other sensors, capable of working alongside humans in critical missions, such as search and rescue. Key requirements are situational awareness and coordinated action. The approach is to develop mathematical frameworks and algorithms to enable such a team of robots to coordinate their paths, share and analyze their sensor data, maintain communications, and interact effectively and safely with humans. The project brings together experts in computer vision, robotics, estimation theory and controls.Intellectual Merit. Realizing the above goals will require advances in several inter-related domains. Specifically, the sensing, estimation, and trajectory control tasks must seamlessly integrate visual analysis with navigation and control strategies, as well as inputs from humans. Novel distributed estimation strategies must be developed to accommodate difficult and dynamic environments. Efficient human-robot coordination necessitates methodologies for joint exploration and mapping, identifying important visual information, and robots? operation at different levels of autonomy.Broader Impact. The success of this project will be a major step towards the deployment of teams of robots to assist humans in dangerous and complex tasks like disaster response. Search-and-rescue experts will advise the team in developing a prototype system, and evaluating it in situations that mimic operational conditions. The developed software tools will be disseminated to other researchers so they can build on the results. Undergraduates from UCR's highly diverse student population will gain valuable experience working alongside graduate student researchers.

这项研究的目标是开发配备视觉和其他传感器的机器人团队，能够在搜索和救援等关键任务中与人类一起工作。关键的要求是了解情况和协调行动。该方法是开发数学框架和算法，使这样的机器人团队能够协调其路径，共享和分析其传感器数据，保持通信，并与人类进行有效和安全的交互。该项目汇集了计算机视觉、机器人、估计理论和控制方面的专家。实现上述目标需要在若干相互关联的领域取得进展。具体来说，传感、估计和轨迹控制任务必须将视觉分析与导航和控制策略以及人类输入无缝集成。必须开发新的分布式估计策略，以适应困难和动态的环境。高效的人机协调需要联合探索和映射的方法，识别重要的视觉信息，和机器人？在不同的自治级别上运行。更广泛的影响。该项目的成功将是部署机器人团队以协助人类完成灾害响应等危险和复杂任务的重要一步。搜救专家将为团队开发原型系统提供建议，并在模拟操作条件的情况下对其进行评估。开发的软件工具将分发给其他研究人员，使他们能够在成果的基础上再接再厉。来自UCR高度多样化的学生群体的本科生将获得与研究生研究人员一起工作的宝贵经验。