Publication
On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis
Conference Article
Conference
Robotics: Science and Systems Conference (RSS)
Edition
2023
Doc link
https://doi.org/10.15607/RSS.2023.XIX.053
File
Authors
Projects associated
Abstract
We present a comprehensive study on discrete morphological symmetries of dynamical systems, which are commonly observed in biological and artificial locomoting systems, such as legged, swimming, and flying animals/robots/virtual characters. These symmetries arise from the presence of one or more planes/axis of symmetry in the system’s morphology, resulting in harmonious duplication and distribution of body parts. Significantly, we characterize how morphological symmetries extend to symmetries in the system’s dynamics, optimal control policies, and in all proprioceptive and exteroceptive measurements related to the system’s dynamics evolution. In the context of data-driven methods, symmetry represents an inductive bias that justifies the use of data augmentation or symmetric function approximators. To tackle this, we present a theoretical and practical framework for identifying the system’s morphological symmetry group G and characterizing the symmetries in proprioceptive and exteroceptive data measurements. We then exploit these symmetries using data augmentation and G-equivariant neural networks. Our experiments on both synthetic and real-world applications provide empirical evidence of the advantageous outcomes resulting from the exploitation of these symmetries, including improved sample efficiency, enhanced generalization, and reduction of trainable parameters.
Categories
robots.
Author keywords
Symmetries, Dynamical Systems
Scientific reference
D.F. Ordoñez, M. Martin, A. Agudo and F. Moreno-Noguer. On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis, 2023 Robotics: Science and Systems Conference, 2023, Daegu, Republic of Korea.
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