Simulators are a critical component of modern robotics research. Strategies for both perception and decision making can be studied in simulation first before deployed to real world systems, saving on time and costs. Despite significant progress on the development of sim-to-real algorithms, the analysis of different methods is still conducted in an ad-hoc manner, without a consistent set of tests and metrics for comparison. This paper fills this gap and proposes a set of benchmarks and a framework for the study of various algorithms aimed to transfer models and policies learnt in simulation to the real world. We conduct experiments on a wide range of well known simulated environments to characterize and offer insights into the performance of different algorithms. Our analysis can be useful for practitioners working in this area and can help make informed choices about the behavior and main properties of sim-to-real algorithms. We open-source the benchmark, training data, and trained models, which can be found at https://github.com/NVlabs/sim-parameter-estimation.
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting
NVIDIA（英伟达）；University of Southern California（南加州大学）；University of Toronto（多伦多大学）；Vector Institute（向量研究所）；University of Washington（华盛顿大学）；University of Sydney（悉尼大学）
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting
University of Southern California（南加州大学）；NVIDIA（英伟达）；University of Washington（华盛顿大学）；University of Toronto（多伦多大学）；Vector Institute（向量研究所）；University of Sydney（悉尼大学）
Machine Learning in Science, University of Tübingen（机器学习科学系，图宾根大学）；Tübingen AI Center（图宾根人工智能中心）；TransferLab, appliedAI Institute for Europe（TransferLab，应用AI欧洲研究所）；Helmholtz AI and Helmholtz-Zentrum Dresden-Rossendorf（海德堡人工智能与德累斯顿-罗斯托克研究中心）；Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France（巴黎-萨克雷大学，法国国家信息与自动化研究所，法国原子能委员会，帕莱伊索，91120）；Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK（格勒诺布尔阿尔卑斯大学，法国国家信息与自动化研究所，国家科学研究中心，格勒诺布尔INP，LJK）；University of Amsterdam（阿姆斯特丹大学）；VIB-Neuroelectronics Research Flanders (NERF), Belgium（比利时弗拉芒神经电子研究VIB-NERF）；Departments of Computer Science and Electrical Engineering, KU Leuven, Belgium（比利时鲁文大学计算机科学与电气工程系）；Google Research（谷歌研究）；Department Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany（经验推理部门，马克斯·普朗克智能系统研究所，图宾根，德国）
