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.

该项目将在固定或移动的任意方向表面上赋予具有自主和普遍栖息能力的小型航空车（例如四轮驱动器），从而扩大了其在侦察，检查，监视，环境监测以及搜索和搜索和搜查领域的运营能力。例如，这将使他们能够降落在一艘船上，船上摇摆着海洋，将搭便车上移动的地面或空中平台，以进行充电或安全性，以帮助人类行李箱轻松地将无人机降落在自我选择的目标上（例如，在墙壁，电力线上，桥下和桥下）。该研究将通过集成的学习框架专注于体现的物理和计算智能的共同设计，以在大多数情况下实现强大的栖息地。该项目还将通过视觉上吸引人的，互动的机器人飞行和栖息实验为K-12学生创建一个STEM教育框架，以在机器人技术，机器学习，机械设计，智能材料和飞行原则中引入多学科概念。此外，研究成果将纳入本科生以及一般劳动力发展的各种教育和宣传模块中，利用NSF新近资助的自主空气流动性和感应中心（CAAMS）（CAAMS）在宾夕法尼亚州立大学的自主空气流动性和感应中心（CAAMS）。触地得分机制对于小型航空车的强烈全向栖息所需的必要。物理智能将通过新颖的起落架系统实现，并具有一系列由生物启发的微型机器人塔西（Tarsi）实现，在达阵期间，可以在现场迅速调整其合规性。将通过学习预测策略区域以及电动机控制的相关政策映射以及2）基于视觉的，基于光学限制的tau指导来通过学习预测策略区域以及相关的策略映射来实现计算智能，从而实现了栖息的角度操纵，并同时将机器人带入目标策略区域和目标登陆地点。最后，计算智能将通过由两层框架组成的物理智能集成：a）机械设计和电动机控制策略以及b）体现和运动控制策略，因为前者将控制生物启发的TARSI合规性，而后者则将控制空中动作。总之，该项目将提高机器人中计算和物理智能之间的共同设计，集成，相互作用和权衡方面的知识，以实现新颖和强大的能力。该项目得到了机器人技术计划的跨指导基础研究的支持，该项目由工程局（ENG）以及计算机和信息科学与工程局（CISE）共同管理和资助。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和更广泛影响的评估来审查Criteria的评估。