NRI:FND:COLLAB: M3SoRo - Mobility and Morphing using Modular Soft Robots

这项国家机器人计划（NRI）的主要目标是开发能够在复杂的陆地和攀爬环境中移动并改变大小和形状的协作模块化软机器人（MSoRos）。一群MSoRos可以用于救灾（搜索和救援行动）、太空探索和精准农业。例如，搜索和救援场景需要小型机器人自主导航洞穴，并在狭窄的裂缝/空间中爬行。协作MSoRos将由柔软的单个单元组成，这些单元可以变形以穿透这些空间，而无需事先规划。在农业中，环境是复杂的，非结构化的（土壤）和不利的（变化包括冷热和降雨），这些机器人模块化设备将能够多种行为来匹配他们的任务。例如，单个模块可以在当地爬行，监测土壤健康状况，然后重新配置成一个三维球，在任务完成后滚动到一个集中的站点。以这种方式形成不同结构的能力可以最大限度地减少运动成本。此外，这项研究很容易在高中生和大学生中传播，因为软机器人便宜，操作安全，有趣。MSoRos将把《变形金刚》（Transformers）或《超能陆战队》（Big Hero 6）等流行的机器人图标与现实生活中的变形软机器人联系起来，从而激发年轻人的思维。同时，它将向他们介绍未来机器人和机电一体化技术，并将其应用于可穿戴机器人、协作机器人和家庭机器人，并鼓励他们在STEM和机器人领域发展事业。这种变形和模块化的结合可以极大地提高机器人的适应性。拟建的研究将：a)学习复杂环境中机器人移动的原理。这类似于构建降阶模型（rom）。高度可变形、柔软、连续机器人的环境特定rom将通过学习主导机器人与环境相互作用的因素进行逆向工程；b)设计开源、不受约束的MSoRos，这将增加传统模块化机器人的多功能性、稳健性和成本效益；C)建立环境意识是控制可变形机器人的有力策略。索罗斯将利用他们与环境的互动来学习和部署适当的行为。这将导致混合机器人的发展，它将以环境为中心的探索性学习（本研究）与现有的以模型为中心的策略相结合，以执行复杂的自主任务。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。

The main objective of this National Robotics Initiative (NRI) award is to develop collaborative Modular Soft Robots (MSoRos) that can move in complex terrestrial and climbing environments and change size and shape. A swarm of MSoRos could be used in disaster relief (search and rescue operations), space exploration and precision agriculture. For example, search and rescue scenarios require small robots to autonomously navigate holes and to crawl through narrow cracks/spaces. The collaborative MSoRos will be composed of soft individual units that can deform to penetrate these spaces without prior programming. In agriculture, where the environment is complex, unstructured (soil) and adverse (changes include heat-cold and rain), these robotic modular devices will be capable of multiple behaviors to match their tasks. For example, individual modules could crawl around locally to monitor soil-health and then re-configure as a three-dimensional ball to roll to a centralized station after the task is complete. The ability to form different structures in this way can minimize locomotion costs. Furthermore, this research is easy to disseminate among high-school and undergraduate students as soft robots are cheap, safe to operate and intriguing. The MSoRos will excite young minds by connecting popular robot icons such as Transformers or Big Hero 6, with real-life morphing soft robots. Simultaneously, it will introduce them to futuristic robotics and mechatronics technologies with applications to wearable robotics, collaborative robotics and robots-in-homes, and encourage them to pursue career in STEM and robotics.This combination of morphing and modularity can dramatically increase the adaptability of a robot. The proposed research will: a) learn principles for robot mobility in complex environments. This is analogous to building reduced-order models (ROMs). Environment-specific ROMs for a highly deformable, soft, continuum robot will be reverse-engineered by learning factors that dominate robot-environment interactions; b) design open-source, untethered MSoRos that will increase the versatility, robustness and cost effectiveness of traditional modular robots; c) establish that environment awareness is a powerful strategy for controlling deformable robots. MSoRos will use their interaction with the environment to learn and deploy appropriate behaviors. This will lead to the development of hybrid robots that will combine environment-centric exploratory learning (this research) with existing model-centric strategies, to carryout complex autonomous tasks.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.