受海樽多喷射推进启发，构建可实现全向运动的仿生机器人控制框架。
Geometric Data-Driven Multi-Jet Locomotion Inspired by Salps
- 基于几何力学设计非轴向控制的多喷射运动模型。
- 仅用三分钟实验数据即精准识别出机器人的阻力主导动力学模型。
- 适合对仿生水下机器人、非线性控制感兴趣的科研人员。
海樽是由一系列类似水母的单元组成的海洋生物，其通过协调多喷射推进实现高效的水下运动，引发机器人领域的广泛关注。本文提出一种受海樽启发的几何力学框架，研究一类新型几何力学模型，其中控制输入不限于形状轴；分析了非线性可控制性，并开发了运动规划与反馈控制方法。我们设计了'LandSalp'机器人，作为海樽游泳简化模型的物理实现，可在无复杂水下干扰因素的情况下评估运动策略。通过结合最小二乘法和基于逆动力学的系统辨识，利用李群微分从实验数据中学习阻力主导模型的黎曼度量。仅需约三分钟的数据，即可准确识别出LandSalp的动力学模型。仿真与硬件实验验证了全向运动、形态调节及弯曲机动能力，为更强大的海樽仿生机器人提供了可遵循的理论路径。
原文摘要 · Abstract (English)
Salps are marine animals consisting of chains of jellyfish-like units. Their efficient underwater locomotion by coordinating multi-jet propulsion has aroused great interest in robotics. This paper presents a geometric mechanics framework for salp-inspired robots. We study a new type of geometric mechanics models inspired by salps, in which control inputs are not restricted to the shape axes, analyze nonlinear controllability, and develop motion planning and feedback control methods. We introduce the "LandSalp" robot, which serves as a physical realization of the reduced-order, drag-dominated model of salp swimming, enabling controlled evaluation of locomotion strategies without many confounding factors of underwater experiments. We extend least-squares- and inverse-dynamics-based system identification to learn the Riemannian metric of the drag-dominated model from experimental data using Lie group differentiation. With about three minutes of data, we identify an accurate model of LandSalp. Simulation and hardware experiments demonstrate omnidirectional locomotion, shape regulation, and bending maneuvers, providing a principled pathway toward more capable salp-inspired robots.
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