面向扑动机器人推进器损伤的生物启发补偿策略
Bio-Inspired Compensatory Strategies for Damage to Flapping Robotic Propulsors
AI总结：
针对扑动机器人推进器损伤补偿问题，采用带硬件在环的协方差矩阵自适应进化策略开展人工进化优化，发现机械推进器的最优损伤补偿策略与自然生物存在差异，为自主机器人自修复设计提供了新依据。
摘要：
为维持完全自主能力，自主机器人系统必须具备自我修复能力。通过补偿机制实现的自我修复在自然界中普遍存在：例如，部分鱼类即使损失76%的推进面积，也能通过改变划动力学机制保持推力不下降。然而，由于存在无关的进化压力，将生物体的这些改变直接迁移到机器人扑动推进器上可能并非最优方案。因此，我们转而通过人工进化的方式，确定受损机器人系统的最优划动力学改变策略。为验证自然最优解与机器学习得到的最优解是否存在差异，我们采用一套信息物理系统，利用协方差矩阵自适应进化策略（Covariance Matrix Adaptation Evolutionary Strategy），针对给定力值寻找最高效的运动轨迹。我们实现了带硬件在环的在线优化，使用一块受驱动的柔性平板开展实验函数评估。在部分切除后为恢复推力输出，学习到的最高效策略为：增大振幅、提高频率、增大攻角振幅，并将攻角相移约110度。而在现有文献中，多数研究表明鱼类仅会通过增大振幅进行补偿。为恢复侧向力输出，我们面临的优化场景更具挑战性。在基于合力的参考系中，我们发现最优攻角轨迹存在嵌套特性，但未观察到振幅或频率的明确变化趋势——这与昆虫相关文献中报道的频率升高现象形成对比。这些结果表明，机械扑动推进器应对损伤的最高效调整方式，可能与自然界的游泳生物和飞行动物并不一致。
英文摘要：
To maintain full autonomy, autonomous robotic systems must have the ability to self-repair. Self-repairing via compensatory mechanisms appears in nature: for example, some fish can lose even 76% of their propulsive surface without loss of thrust by altering stroke mechanics. However, direct transference of these alterations from an organism to a robotic flapping propulsor may not be optimal due to irrelevant evolutionary pressures. We instead seek to determine what alterations to stroke mechanics are optimal for a damaged robotic system via artificial evolution. To determine whether natural and machine-learned optima differ, we employ a cyber-physical system using a Covariance Matrix Adaptation Evolutionary Strategy to seek the most efficient trajectory for a given force. We implement an online optimization with hardware-in-the-loop, performing experimental function evaluations with an actuated flexible flat plate. To recoup thrust production following partial amputation, the most efficient learned strategy was to increase amplitude, increase frequency, increase the amplitude of angle of attack, and phase shift the angle of attack by approximately 110 degrees. In fish, only an amplitude increase is reported by majority in the literature. To recoup side-force production, a more challenging optimization landscape is encountered. Nesting of optimal angle of attack traces is found in the resultant-based reference frame, but no clear trend in amplitude or frequency are exhibited -- in contrast to the increase in frequency reported in insect literature. These results suggest that how mechanical flapping propulsors most efficiently adjust to damage of a flapping propulsor may not align with natural swimmers and flyers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
