用最优控制优化三连杆微泳机器人,提升移动效率与距离。
Optimal control of a swimming robot based on Purcell's microswimmer model

- 基于庞特里亚金极小值原理设计最优摆动模式
- 在关节角度约束下实现单周期最大位移与能量效率
- 适合对微流体机器人运动优化感兴趣的工程师
Purcell微泳器是经典平面微尺度游泳模型,由三个通过可驱动旋转关节连接的刚性杆组成,遵循低雷诺数流体动力学。本文实现了该模型在高粘性流体中的宏观机器人实体,并提出一种改进版本,包含非细长杆和中央刚性球体以模拟浮力块带来的额外阻力,通过实验数据校准模型参数。采用庞特里亚金最大值原理(PMP)构建最优控制框架,求解在关节角限制下最大化单周期位移的最优步态。利用微分几何方法将问题转化为关节平面内轨迹围成的面积积分,实现步态拓扑变化的直观解释。进一步将目标转为最大化Lighthill能量效率,导出边界值问题(BVP),求解得到原模型及改进模型的效率最优步态。通过截断傅里叶级数参数化输入,并结合GPOPS-II求解器,生成足够初值以求解BVP,获得高效步态。
原文摘要 · Abstract (English)
Purcell's swimmer is a well-known planar model of a swimming microorganism, governed by low Reynolds number hydrodynamics, which is comprised of three rigid links connected by actuated rotary joints. This model has been analyzed as a robotic locomotion system governed by first-order nonlinear dynamics with a periodic input (gait) of the two joint angles. In this work, we present a robotic macro-scale realization of this three-link swimmer moving in a highly viscous fluid. We propose a simple variant of Purcell's theoretical model with non-slender links and a central rigid sphere which represents the added drag of the robot's central flotation block, and calibrate the model's parameters to fit experimental measurements. Next, we apply optimal control formulation based on Pontryagin's Maximum Principle (PMP) in order to find optimal gaits that maximize the displacement per cycle under bounds on the joint angles. Employing a differential geometric method that transforms the problem to area integral enclosed by the gait trajectory in the plane of joint angles, enables visual interpretation which explains topological changes in displacement-optimal gaits upon varying the bound on the joint angles. We then apply PMP formulation to the problem of maximizing Lighthill's energy efficiency in order to obtain a boundary value problem (BVP) whose solution gives efficiency-optimal gaits for Purcell's swimmer model, as well as its variant with a central sphere. Finally, we utilize numerical methods such as parameterizing the input gait as a truncated Fourier series, as well as GPOPS-II solver, to produce sufficient initial guess values for solving the BVPs and obtaining efficiency-optimal gaits.
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