Collaborative Research: Design, Flight Control, and Autonomous Navigation of Bioinspired Morphing Micro Aerial Vehicles for Operation in Confined Spaces

该项目将推动空中机器人科学的进步，促进国家繁荣和福利，创造出受蝙蝠启发的无人机，可以在极其狭小的空间中操作。城市下水道对快速、持续的环境监测的需求越来越大。这些狭小的空间占据了城市基础设施的很大一部分。然而，今天的传统机器人，包括地面和空中系统，不能在绝大多数下水道中操作。下水道网络呈现了一个名副其实的管道、房间和公用设施洞的迷宫，给机器人的运动控制和导航带来了巨大的挑战。因此，人类操作员仍然会检查这些危险的空间。除了给人类带来许多风险外，在这些环境中进行载人操作既昂贵又缓慢。这项拨款的研究将有助于设计以蝙蝠为灵感的空中机器人，通过模仿蝙蝠在洞穴中的空中运动原理，在下水道中操作。这项研究的结果将极大地造福社会。特别是在大流行期间，使用这些以蝙蝠为灵感的无人机对城市老化的下水道系统进行持续自动监测，可以在拯救人类生命方面发挥至关重要的作用。例如，SARS-CoV可以在废水中存在数天，2019年在下水道中及早检测到它，本可以加强抗击当前大流行的准备。该项目培养具有跨学科技能的新一代科学家、工程师和技术人员，为未来的专业人员提供垂直集成的、以使用为灵感的体验式学习活动。今天的旋转翼无人机是检查和监测城市基础设施的更好的解决方案，因为它们可扩展、廉价、易于部署，并且具有快速的机动性。然而，这些系统不能在狭窄的区域内飞行，比如小横截面的隧道，因为它们依赖于强大而持续的空气喷流。到目前为止，这些无人机的受限空间应用仅包括在建筑物内或非常宽敞的受限环境中飞行，这与空中机器人在下水道中的应用无法相提并论。这项研究将允许无人机在狭窄的空间内完成完全自主的飞行，比如下水道走廊。研究小组将(I)使用集成的机械智能和控制框架来设计具有动态多功能机身结构和显著计算复杂性的无人机，以防止产生强大的喷气式飞机；(Ii)设计基于模型和数据驱动的集成飞行控制框架，不仅捕获模型的不确定性，还捕获因在隧道中飞行而产生的环境空气动力学影响；以及(Iii)开发一种新型导航框架，该框架依赖于从下水道示意图中提取的高级抽象指导，从而能够在未绘制的环境中进行稳健的导航。该项目得到了跨部门的机器人基础研究计划的支持，该奖项由工程指导委员会(ENG)和计算机与信息科学与工程委员会(CEISE)共同管理和资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will promote the progress of science in aerial robotics and advance the national prosperity and welfare, by creating bat-inspired drones that can operate in extremely confined spaces. There is an increased demand for fast, continuous environmental surveillance in city sewers. These confined spaces occupy a large portion of a city's infrastructure. However, today's conventional robots, including ground and aerial systems, cannot operate in a vast majority of sewers. Sewer networks present a veritable maze of pipes, chambers, and utility holes that pose tremendous challenges for robot locomotion control and navigation. Therefore, human operators still inspect these dangerous spaces. In addition to carrying many risks for humans, manned operations in these environments are costly and slow. This grant’s research will contribute to the design of aerial, bat-inspired robots that can operate in sewers, by mimicking bat aerial locomotion principles in caves. The results from this research will greatly benefit the society. Especially during a pandemic, the continuous and automated monitoring of a city’s aging sewer systems using these bat-inspired drones can play a vital role in saving human lives. For instance, SARS-CoVs can be present in wastewater for several days, and its early detection in sewers in 2019 could have allowed for increased preparedness in combating the current pandemic. This project trains new generation scientists, engineers, and technologists with interdisciplinary skills, providing future professionals with vertically integrated, use-inspired experiential learning activities.Today's rotary-wing drones are better solutions for inspection and monitoring city infrastructure than ground robots because they are scalable, inexpensive, easy to deploy, and possess fast mobility. However, these systems cannot fly inside tight areas such as tunnels with small cross-sections because they rely on powerful and continuous air jets. So far, the confined space applications of these drones include only flying inside buildings or very spacious confined environments, which are not comparable to the application of aerial robots in sewers. This research will allow drones to complete fully autonomous flights inside tight spaces such as sewer galleries. The research team will (i) use an integrated mechanical intelligence and control framework to design drones with dynamically versatile body conformations and significant computational complexity to prevent creation of powerful air jets, (ii) design an integrated model-based and data-driven flight control framework that captures not only the model uncertainty but also the environmental aerodynamic effects that arise due to flight in tunnels, and (iii) develop a novel navigation framework that relies on high-level abstract guidance extracted from sewer schematic diagrams, enabling robust navigation in unmapped environments.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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.