NRI: FND: Natural Power Transmission through Unconstrained Fluids for Robotic Manipulation

这一国家机器人倡议项目将促进科学进步，促进国家健康、繁荣和福利；研究一种新的方法，通过不受限制的水流控制机器人的动力传输，使用流固相互作用控制策略，而不需要任何其他直接接触来操纵对象。在许多现有的机器人控制问题中，动力是通过与被操纵对象直接接触来传递的。本项目的重点是水下操纵的情况，其中环境(水)对整个系统的性能有重大影响。在以流体为基础的系统中，物体与其周围流体之间的相互作用将大量的动量转移到水中。在这项工作中，水中的物体将通过操纵上游结构来控制，该结构的尾迹可以控制。上游物体的尾迹将通过强迫其以给定的频率和角速度旋转来控制。通过闭环反馈，通过输入上游结构物的期望运动，从而控制其尾迹，即可获得下游物体的期望运动。该方法可用于为中风或损伤恢复者建立一种新的自然和无约束的步态训练方法，通过使用流动力自然地辅助他们的步态。除了健康，这项工作的扩展可以应用于制造，以创造基于流体的材料处理和生产过程的新方法。该项目还将通过培训本科生和研究生，以及为K-12学生设计和实施创新的水下机器人推广计划，来激励和拓宽下一代工程师和科学家的多样性。这项工作对机器人的变革性影响正在使一种新的基于流体的非接触操纵策略成为可能。这项工作在流体-结构相互作用领域创造了新的见解，通过引入闭环控制方法来间接施加放置在另一结构后面的对象的期望运动。采用“探索-开发”的方法有效地搜索高度非线性系统中的参数，以实现受控旋转圆柱尾迹的水翼的最优极限环振动。然后可以利用这些参数设计控制器，通过控制上游气缸的转速来获得多体系统的期望轨迹。通过这种方法，可以创建一个水下机器人步态训练系统，该系统可以操纵现有流体的力量，向人的下肢施加受控力量，以帮助他们行走。该系统由新的水下人体步态预测模拟和流固耦合动力学支持，以优化互联的人-机器人系统。该方法也可以推广到水下机器人中使用流体力进行非接触操纵的其他应用。该奖项反映了NSF的法定使命，并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，被认为值得支持。

This National Robotics Initiative project will promote the progress of science and advance the national health, prosperity and welfare; by studying a novel approach to control the transmission of power from a robot through an unconstrained flow of water to manipulate an object using fluid-structure interaction control strategies and without any other direct contact. In many existing robotic control problems, power is transferred through direct contact with the object to be manipulated. This project focuses on the case of underwater manipulation, where the environment (water) has a significant impact on the overall system performance. In a fluid-based system, interactions between bodies and fluid around them transfer a significant amount of momentum to the water. In this work, an object in water will be controlled by manipulating an upstream structure whose wake can be controlled. The wake of the upstream object will be controlled by forcing it to rotate at a given frequency and angular velocity. Through closed-loop feedback, the desired motion of the downstream object can be obtained by inputting the desired motion of the upstream structure and thus controlling its wake. The approach can be applied to establish a novel method for natural and unconstrained gait training for persons recovering from stroke or injury by naturally assisting their gait using flow forces. Beyond health, extensions of this work can be applied in manufacturing to create new methods for fluid-based material handling and production processes. The project will also motivate and broaden the diversity of the next generation of engineers and scientists through training undergraduate and graduate students and designing and implementing an innovative underwater robotics outreach program for K-12 students. The transformative impact of this work on robotics is enabling a new fluid-based, non-contact manipulation strategy. The work creates new insights in the field of fluid-structure interactions by introducing a closed-loop control method to indirectly impose desired motions of an object placed in the wake of another structure. An “explore-and-exploit” methodology is used to effectively search for parameters in the highly nonlinear system to achieve optimal limit cycle oscillations of a hydrofoil in the wake of a controlled rotating cylinder. The parameters can then be used to design a controller to obtain the desired trajectory for a multi-body system by controlling the rotation rate of an upstream cylinder. With this approach, an underwater robot gait training system is created that can manipulate the power of the existing fluid flow to apply controlled forces to the lower limbs of a person to assist them while walking. The system is supported by new predictive simulations of underwater human gait with fluid-structure interaction dynamics to optimize the interconnected human-robot system. The approach can also be generalized for other applications in underwater robotics for non-contact manipulation using flow forces.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.