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arXiv 2402.15552cs.ROcs.AIcs.SYeess.SY
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机器人学中的形态对称性

Morphological Symmetries in Robotics

Istituto Italiano di Tecnologia (IIT)(意大利技术研究院(IIT));Institut de Robòtica i Informàtica Industrial, CSIC-UPC(西班牙国家研究委员会-加泰罗尼亚理工大学机器人与信息自动化研究所);Heriot-Watt University(赫瑞瓦特大学)

Daniel Ordoñez-Apraez, Giulio Turrisi, Vladimir Kostic, Mario Martin, Antonio Agudo, Francesc Moreno-Noguer, Massimiliano Pontil, Claudio Semini, Carlos Mastalli

AI总结:

本文提出形态对称性作为机器人学中的物理信息几何先验,通过数据增强或架构约束提升数据驱动方法的效率,并利用抽象调和分析分解动力学,在双足和四足机器人上验证,并发布MorphoSymm仓库。

摘要:

我们提出了一个用于研究和利用机器人系统中形态对称性的综合框架。这些对称性是机器人形态的内在属性,在动物生物学和机器人学中经常观察到,源于运动学结构的重复和质量分布的对称性。我们阐述了这些对称性如何扩展到机器人的状态空间以及本体感觉和外感觉传感器测量,导致机器人运动方程和最优控制策略的等变性。因此,我们将形态对称性视为一种相关且先前未探索的物理信息几何先验,对机器人建模、控制、估计和设计中使用的数据驱动和分析方法具有重要影响。对于数据驱动方法,我们证明形态对称性可以通过数据增强或对模型架构施加等变/不变约束来提高机器学习模型的样本效率和泛化能力。在分析方法方面,我们采用抽象调和分析将机器人动力学分解为低维独立动力学的叠加。我们通过在双足和四足机器人上进行的合成和真实世界实验来证实我们的主张。最后,我们介绍了MorphoSymm仓库,以促进本工作中所述理论和应用的实际使用。

英文摘要:

We present a comprehensive framework for studying and leveraging morphological symmetries in robotic systems. These are intrinsic properties of the robot's morphology, frequently observed in animal biology and robotics, which stem from the replication of kinematic structures and the symmetrical distribution of mass. We illustrate how these symmetries extend to the robot's state space and both proprioceptive and exteroceptive sensor measurements, resulting in the equivariance of the robot's equations of motion and optimal control policies. Thus, we recognize morphological symmetries as a relevant and previously unexplored physics-informed geometric prior, with significant implications for both data-driven and analytical methods used in modeling, control, estimation and design in robotics. For data-driven methods, we demonstrate that morphological symmetries can enhance the sample efficiency and generalization of machine learning models through data augmentation, or by applying equivariant/invariant constraints on the model's architecture. In the context of analytical methods, we employ abstract harmonic analysis to decompose the robot's dynamics into a superposition of lower-dimensional, independent dynamics. We substantiate our claims with both synthetic and real-world experiments conducted on bipedal and quadrupedal robots. Lastly, we introduce the repository MorphoSymm to facilitate the practical use of the theory and applications outlined in this work.

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。

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