CAREER: Designing Autonomous Battery-Free Robotic Sensors

微型机器人传感器在许多应用中具有变革潜力。与设计用于在特定位置进行测量的固定物联网传感器不同，机器人可以移动到不同的位置进行采样。这些机器人有可能在道路、桥梁和铁路上进行基础设施检查，跟踪仓库货架上的库存，测量农场的环境条件，在有毒化学品或强电磁场的工业场景中进行测量，甚至用于太空探索。机器人传感器也可以移动以寻找火灾或气体泄漏的来源。传统机器人的核心部件是提供电力和能量的电池。然而，电池限制了机器人在远程环境中操作的时间和范围。对于小型微型机器人来说，电池也很难分解，而且由于使用有毒和稀缺的关键材料，电池的制造和处置也会对环境产生重大影响。该学院的早期职业发展（CAREER）研究旨在开发一类新的免维护机器人传感器，该传感器由使用太阳能电池或无线电发射器的光等来源收集的能量驱动。关键的实现思想是以离散的步骤操作这些机器人，从而使运动能够获得少量的能量，但实现这一目标需要重新设计机器人机制，电路和控制算法。这项跨学科的研究将建立设计无电池机器人的基础技术，从机械部件和电路到控制软件。通过重新设计传统的机器人子系统与能量收集的兼容性，本研究将有助于以下方面：1）离散化与电子和结构能量存储协同优化的机器人运动的策略，并研究这些方法如何随机器人尺寸而扩展; 2）用新的能量收集方法为机器人供电的方法，并优化机器人运动的电源管理算法。3)该项目的主要目标是：1）开发无电池机器人的感知能力，如车载视觉或气味分类，并探索无线连接的多机器人架构; 2）探索基于人工智能的工具和工作流程，用于机器人和嵌入式系统设计、代码生成、电源优化和调试; 3）开发与间歇运动兼容的控制系统。这项研究还将通过用于算法开发和教育的可编程机器人原型平台，与本科生和K-12学生的教育经验紧密结合。本科生研究人员将帮助开发机器人平台，推广活动将与非营利教育组织合作进行，如电子扫盲和访问的愿景。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Miniaturized robotic sensors have transformative potential for numerous applications. Unlike fixed Internet of Things sensors designed to take measurements in a specific location, a robot can move to sample different locations. Such robots have potential to perform infrastructure inspection on roadways, bridges, and railroads, track inventory on warehouse shelves, measure environmental conditions on farms, take measurements in industrial scenarios with toxic chemicals or strong electromagnetic fields, or even be used in space exploration. Robotic sensors could also move to seek out sources of fires or gas leaks. A core component of traditional robots is a battery that provides power and energy. Batteries however limit the time and range at which a robot can operate in remote environments. Batteries are also difficult to miniaturize for small microrobots, and battery manufacturing and disposal also have significant environmental impacts due to the use of toxic and scarce critical materials. This Faculty Early Career Development (CAREER) research seeks to develop a new class of maintenance-free robotic sensors powered by energy harvested from sources like light using solar cells or from radio transmitters. The key enabling idea is to operate these robots in discrete steps which enables motion with small amounts of harvested energy, but achieving this requires redesigning robot mechanisms, circuits, and control algorithms. This interdisciplinary research will establish fundamental techniques for designing battery-free robots ranging from mechanical components and circuits to control software. By redesigning conventional robot sub-systems for compatibility with energy harvesting this research will contribute to the following: 1) strategies to discretize robot motion co-optimized with electronic and structural energy storage and investigate how these methods scale versus robot size; 2) methods to power robots with novel energy harvesting approaches and optimizing power management algorithms for robot motion. 3) perception capabilities for battery-free robots such as onboard vision or odor classification and explore wirelessly connected multi-robot architectures; 4) explore AI based tools and workflows for robot and embedded system design, code generation, power optimization, and debugging; 5) Develop control systems compatible with intermittent motion. This research will also be closely coupled to educational experiences for undergraduates and K-12 students through a programmable robot prototyping platform for algorithm development and education. Undergraduate researchers will help develop the robot platform and outreach activities will be conducted in partnership with nonprofit educational organizations such as A Vision for Electronic Literacy and Access.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.