CAREER: Architectures of Responsiveness: Coordinating Primitives for Soft Robot Locomotion in Confined Spaces

这个教师早期职业发展计划（Career）项目将为密闭空间中的机器人运动创建一个词汇表，从而实现新型的医疗保健和基础设施检查系统。蚯蚓等动物柔软的身体使它们能够穿过狭窄的空间，并通过复杂的障碍物。软机器人有潜力通过被动机械顺应和主动响应的结合来模仿这些能力。就像它们的生物类似物一样，这些机器人在移动过程中不断地与周围环境建立或断开联系。结构软系统的高自由度，加上动态变化的接触点，使得这类机器人运动的集中控制成为一个棘手的问题。相比之下，对蚯蚓等动物的研究表明，复杂的全身动作可能是由单个身体部位的简单运动的集体行动产生的。受此示例的启发，该项目将开发动态丰富但易于计算的局部响应原语的可组合架构，这些原语将组合产生所需的运动。这些架构将为一个正在进行的项目提供基础，该项目将把软体动物的运动策略转化为新型智能和反应灵敏的机器人。该研究项目还辅之以一项教育计划，为那些希望为科学做出贡献的学生——包括在家学习的学生——提供一种替代传统“管道”模式的方法。其目标是在科学家、工程师和学生之间建立现场联系，以提高对科学研究的认识，扩大STEM职业的准入，并培养公众对社区的信任，否则这些社区很少见到科学家。这个项目的中心假设是，在状态空间的鞍点周围构建响应运动原语，将使可组合动态响应的架构变得特别丰富和通用。使用鞍而不是典型的稳定吸引子，可以使感官输入在不改变潜在动力学的情况下影响轨迹，从而在更大的网络中实现更模块化的控制。这将通过开发工具来协调体系结构中的控制原语来证明，这些体系结构在空间上为许多自由度进行缩放，在层次上为广泛的传感器信息进行缩放，在拓扑上为决策进行缩放。不同的缩放方法将通过在密闭空间中增加对蚯蚓运动的响应性来验证和演示。响应局部破坏的相邻段的空间补充将解决滑移问题。分层嵌套响应将解决被动转向与主动转向之间的竞争。拓扑可切换共识将使不同的策略（例如，支撑与波动和蠕动步态）适应不同的环境。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。

This Faculty Early Career Development Program (CAREER) project will create a vocabulary for robot motion in confined spaces, enabling new types of healthcare and infrastructure inspection systems. The soft bodies of animals such as earthworms allow them to travel through narrow spaces and to navigate complex arrangements of obstacles. Soft robots have the potential to emulate those capabilities through the combination of passive mechanical compliance and active response. Like their biological analogs, these robots continually make and break contact with their surroundings as they move. The high number of degrees of freedom of structurally soft systems, combined with the dynamically changing contact points, makes centralized control of this type of robot motion an intractable problem. In contrast, studies of animals such as earthworms have shown that complex whole-body maneuvers may be generated as the collective action of simple movements of individual body segments. Inspired by this example, this project will develop composable architectures of dynamically rich, but easily computed local response primitives that will combine to produce desired motions. These architectures will provide the basis for an on-going project to translate the locomotion strategies of soft-bodied animals into new classes of intelligent and responsive robots. The research program is complemented by an educational plan to provide an alternate to traditional "pipeline" models for students who want to contribute to science -- including students learning from home. The goal is to create in-place connections between scientists, engineers, and students to increase awareness of scientific research, expand access to STEM careers, and foster public trust in communities that would otherwise rarely meet scientists. The central hypothesis of this project is that building responsive movement primitives around saddle points in state space will enable an especially rich and versatile architecture of composable dynamic response. Using saddles instead of the typical stable attractors enables sensory input to influence trajectories without altering underlying dynamics, leading to more modular control within a larger network. This will be demonstrated by developing tools to coordinate control primitives in architectures that scale spatially for many degrees of freedom, hierarchically for broad sensor information, and topologically for decision-making. The different scaling approaches will be validated and demonstrated by adding responsiveness to earthworm-like locomotion for confined spaces. Spatial recruitment of neighboring segments in response to local failures will address the problem of slip. Hierarchical nested responsiveness will resolve competition between passive vs active turning. Topological switchable consensus will enable qualitatively different strategies (e.g. bracing with undulation versus peristaltic gaits) to suit different environments.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.