TacEx: Isaac SimにおけるGelSight触覚シミュレーション — ソフトボディと視触覚シミュレータの統合
TacEx: GelSight Tactile Simulation in Isaac Sim -- Combining Soft-Body and Visuotactile Simulators
Isaac Simにソフトボディ接触シミュレータGIPCと視触覚シミュレータTaxim/FOTSを組み込み、GelSight Miniの触覚を高精度に再現するモジュール式シミュレーションフレームワークTacExを開発し、強化学習環境でその有効性を検証した。
著者: Duc Huy Nguyen, Tim Schneider, Guillaume Duret, Alap Kshirsagar, Boris Belousov, Jan Peters
分類: cs.RO
原文アブストラクト
Training robot policies in simulation is becoming increasingly popular; nevertheless, a precise, reliable, and easy-to-use tactile simulator for contact-rich manipulation tasks is still missing. To close this gap, we develop TacEx -- a modular tactile simulation framework. We embed a state-of-the-art soft-body simulator for contacts named GIPC and vision-based tactile simulators Taxim and FOTS into Isaac Sim to achieve robust and plausible simulation of the visuotactile sensor GelSight Mini. We implement several Isaac Lab environments for Reinforcement Learning (RL) leveraging our TacEx simulation, including object pushing, lifting, and pole balancing. We validate that the simulation is stable and that the high-dimensional observations, such as the gel deformation and the RGB images from the GelSight camera, can be used for training. The code, videos, and additional results will be released online https://sites.google.com/view/tacex.
