Collaborative Research: Omnidirectional Perching on Dynamic Surfaces: Emergence of Robust Behaviors from Joint Learning of Embodied and Motor Control

合作研究：动态表面上的全方位栖息：从具身控制和运动控制的联合学习中出现鲁棒行为

• 批准号: 2230320
• 负责人: Bo Cheng
• 金额: $ 70万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230320&HistoricalAwards=false
• 关键词: Collaborative; Research; Omnidirectional; Perching; Dynamic

This project will endow small aerial vehicles (e.g., quadcopters) with autonomous and universal perching capability on stationary or moving surfaces of arbitrary orientations, thereby expanding their operational capabilities in the areas of reconnaissance, inspection, surveillance, environmental monitoring, and search and rescue. For example, it will enable them to land on a sailing ship that heaves and sways with the sea, to hitchhike onto a moving ground or aerial platform for charging or safety, to assist a human-pilot to easily land a drone on self-selected targets (e.g., on walls, powerlines, and underneath a bridge). The research will focus on the co-design of embodied physical and computational intelligence through an integrated learning framework to achieve robust perching in most circumstances. The project will also create a STEM educational framework for K-12 students through visually appealing, interactive robotic flight and perching experiments to introduce multidisciplinary concepts in robotics, machine learning, mechanical design, smart materials, and flight principles. Furthermore, the research outcomes will be integrated into various educational and outreach modules for undergraduate students as well as general workforce development, leveraging the newly NSF-funded Center for Autonomous Air Mobility and Sensing (CAAMS) at Pennsylvania State University.The objective of this research is to combine the design and learning modalities of both physically embodied intelligence and computational intelligence to enable a wide range of dynamic touchdown mechanisms necessary for robust omnidirectional perching of small aerial vehicles. Physical intelligence will be achieved via a novel landing gear system with an array of bio-inspired, miniature robotic tarsi, whose compliance can be rapidly tuned on the spot during the touchdown. Computational intelligence will be achieved via 1) the initiation and control of perching angular maneuvers by learning predictive policy regions and the associated policy mapping for motor control and 2) vision based, optical-flow-constrained tau-guidance that simultaneously brings a robot into the target policy region and the target landing location. Finally, computational intelligence will be integrated with physical intelligence through a two-layered framework composed of joint learning of: a) mechanical design and motor control policies and b) embodied and motor control policies, respectively, as the former component would control the bio-inspired tarsi compliance and the latter would control the aerial maneuvers. In conclusion, this project will advance knowledge in the co-design, integration, interplay, and trade-offs between computational and physical intelligence in robots to achieve novel and robust capabilities. 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.

该项目将赋予小型飞行器（例如四轴飞行器）在任意方向的静止或移动表面上自主且通用的栖息能力，从而扩展其在侦察、检查、监视、环境监测和搜救等领域的作战能力。例如，它将使他们能够降落在随海水起伏和摇摆的帆船上，搭便车到移动的地面或空中平台上进行充电或安全，协助飞行员轻松地将无人机降落在自选的飞机上。目标（例如，墙壁上、电线上和桥下）。该研究将侧重于通过集成学习框架对实体物理和计算智能进行协同设计，以在大多数情况下实现稳健的栖息。该项目还将通过视觉吸引力、交互式机器人飞行和栖息实验，为 K-12 学生创建一个 STEM 教育框架，介绍机器人、机器学习、机械设计、智能材料和飞行原理方面的多学科概念。此外，利用美国国家科学基金会 (NSF) 新资助的宾夕法尼亚州立大学自主空气流动和传感中心 (CAAMS)，研究成果将被整合到本科生的各种教育和外展模块以及一般劳动力发展中。 这项研究的目标是将物理体现智能和计算智能的设计和学习模式结合起来，以实现小型飞行器稳健的全向栖息所需的各种动态着陆机制。物理智能将通过一种新颖的起落架系统来实现，该系统具有一系列仿生微型机器人跗节，其顺应性可以在着陆期间当场快速调整。计算智能将通过以下方式实现：1）通过学习预测策略区域和相关的运动控制策略映射来启动和控制栖息角度机动；2）基于视觉、光流约束的 tau 引导，同时将机器人带入目标政策区域和目标落地地点。最后，计算智能将通过一个两层框架与物理智能集成，该框架由联合学习组成：a）机械设计和运动控制策略以及b）体现和运动控制策略，因为前一个组件将控制生物激发跗节的顺从性，后者将控制空中机动。总之，该项目将推进机器人的协同设计、集成、相互作用以及计算智能和物理智能之间的权衡方面的知识，以实现新颖而强大的功能。该项目得到了机器人学跨部门基础研究项目的支持，该项目由工程理事会 (ENG) 和计算机与信息科学与工程理事会 (CISE) 共同管理和资助。该奖项反映了 NSF 的法定使命，并被认为值得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来提供支持。