CPS: Medium: Aerial Co-Workers: Augmenting Physical and Cognitive Human Capabilities

该项目研究算法基础和方法框架，通过人类和多智能体机器人系统之间的物理和认知协作的新形式来增强人类的能力，创建空中同事。这些机器将积极地相互协作，并与人类合作，并在物理和认知层面解决与人类- mav协作相关的基本差距。该项目由两个主要领域组成：物理协作和认知协作。第一个目标是通过利用操作员与相互连接的四旋翼机网络之间的物理协作来显著增强人类工人的身体能力，四旋翼机配备了一套“飞行手”，用于运输物体。这将为人机协作提供新颖的科学解决方案，以解释运动的复杂易读性，以及代理相对位置的可变性。第二个重点是解决两个感知共识问题，使mav辅助增强现实（AR）能够增强操作员的认知能力。关键是通过多个MAVs一致地收集、分析和显示上下文信息，以实现有效和自然的人机视觉交互。“空中同事”将获得对人类遮挡的环境的有利视角，这些视角可以在工作空间中直接进行定制和增强，从而通过新颖的度量语义协同空间映射促进人类的行动。该项目作为一项颠覆性技术，将对工业和建筑市场产生巨大的社会影响，迫切需要创新的解决方案，以提高效率，同时最大限度地提高安全性。其结果将使维护、检查、运输、搜索和救援等场景的任务执行更安全、更快、更简单。该项目将通过在开源论坛上提供硬件设计、算法、数据集和代码，为机器人、计算机视觉和机器学习领域的新研究人员降低障碍。这个项目中使用的AR工具和四旋翼飞行器的有趣性质将有助于吸引K-12和大学生观众。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project studies the algorithmic foundations and methodological frameworks to augment human capabilities via a novel form of physical and cognitive collaboration between human and multi-agent robotic systems, creating Aerial Co-Workers. These machines will actively collaborate with each other and with humans and tackle the fundamental gaps related to human-MAV collaboration at both physical and cognitive levels. The project is organized along two main thrust areas: Physical Collaboration and Cognitive Collaboration. The first thrust aims to significantly augment the physical ability of human workers by taking advantage of physical collaboration between the operator and a network of interconnected quadrotors, equipped with a set of flying hands", transporting objects. This will produce novel scientific solutions for human-robot collaborations to account for the complex legibility of the motions, and the variability of the relative positions of the agents. The second thrust aims to address two perception consensus problems to enable MAV-assisted augmented reality (AR) to augment the cognitive ability of operator(s). The key is to consistently collect, analyze, and display contextual information via multiple MAVs for effective and natural human-robot visual interactions. Aerial Co-Workers will get vantage viewpoints of the environment occluded from the humans which can be customized and augmented directly in the workspace to facilitate human actions via novel metric-semantic collaborative space mapping.This project will have a strong societal impact as a disruptive technology for industry as well as the construction market, which is in urgent need of innovative solutions for enhancing the efficacy while maximizing safety. The outcome will enable safer, faster, and simpler task execution in scenarios including maintenance, inspection, transportation, and search and rescue. The project will contribute to lowering the barriers for new researchers in robotics, computer vision, and machine learning by making hardware designs, algorithms, datasets, and code available on open-source forums. The playful nature of AR tools and quadrotors employed in this project will contribute to engaging K-12 and undergraduate audiences.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.