AUTHOR=Ghaffari Maani , Zhang Ray , Zhu Minghan , Lin Chien Erh , Lin Tzu-Yuan , Teng Sangli , Li Tingjun , Liu Tianyi , Song Jingwei TITLE=Progress in symmetry preserving robot perception and control through geometry and learning JOURNAL=Frontiers in Robotics and AI VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2022.969380 DOI=10.3389/frobt.2022.969380 ISSN=2296-9144 ABSTRACT=

This article reports on recent progress in robot perception and control methods developed by taking the symmetry of the problem into account. Inspired by existing mathematical tools for studying the symmetry structures of geometric spaces, geometric sensor registration, state estimator, and control methods provide indispensable insights into the problem formulations and generalization of robotics algorithms to challenging unknown environments. When combined with computational methods for learning hard-to-measure quantities, symmetry-preserving methods unleash tremendous performance. The article supports this claim by showcasing experimental results of robot perception, state estimation, and control in real-world scenarios.