HyperSurf: GRUと実機-シミュレーション転移による表面認識が可能な四足歩行ロボットの脚
HyperSurf: Quadruped Robot Leg Capable of Surface Recognition with GRU and Real-to-Sim Transferring
四足歩行ロボットの脚で表面を認識するため、交換可能な表面を踏める単脚装置とGRUベースの認識システムを開発し、実機からシミュレーションへの表面特性転移を可能にした。
著者: Sergei Satsevich, Yaroslav Savotin, Danil Belov, Elizaveta Pestova, Artem Erhov, Batyr Khabibullin, Artem Bazhenov, Vyacheslav Kovalev, Aleksey Fedoseev, Dzmitry Tsetserukou
分類: cs.RO
原文アブストラクト
This paper introduces a system of data collection acceleration and real-to-sim transferring for surface recognition on a quadruped robot. The system features a mechanical single-leg setup capable of stepping on various easily interchangeable surfaces. Additionally, it incorporates a GRU-based Surface Recognition System, inspired by the system detailed in the Dog-Surf paper. This setup facilitates the expansion of dataset collection for model training, enabling data acquisition from hard-to-reach surfaces in laboratory conditions. Furthermore, it opens avenues for transferring surface properties from reality to simulation, thereby allowing the training of optimal gaits for legged robots in simulation environments using a pre-prepared library of digital twins of surfaces. Moreover, enhancements have been made to the GRU-based Surface Recognition System, allowing for the integration of data from both the quadruped robot and the single-leg setup. The dataset and code have been made publicly available.
