Robot Learning From Randomized Simulations: A Review

Data-Efficient Domain Randomization With Bayesian Optimization

(2021) Fabio Muratore et al.   IEEE Robotics and Automation Letters

The frontier of simulation-based inference

(2020) Kyle Cranmer et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?

(2020) Abhishek Kadian et al.   IEEE Robotics and Automation Letters

A Comprehensive Survey on Transfer Learning

(2020) Fuzhen Zhuang et al.   PROCEEDINGS OF THE IEEE

A Differentiable Physics Engine for Deep Learning in Robotics

(2019) Jonas Degrave et al.   Frontiers in Neurorobotics

Learning dexterous in-hand manipulation

(2019) OpenAI: Marcin Andrychowicz et al.   INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

A Survey on Policy Search Algorithms for Learning Robot Controllers in a Handful of Trials

(2019) Konstantinos Chatzilygeroudis et al.   IEEE Transactions on Robotics

Assessing Transferability From Simulation to Reality for Reinforcement Learning

(2019) Fabio Muratore et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection

(2017) Sergey Levine et al.   INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

Predictable behavior during contact simulation: a comparison of selected physics engines

(2016) Se-Joon Chung et al.   COMPUTER ANIMATION AND VIRTUAL WORLDS

The DARPA Robotics Challenge Finals: Results and Perspectives

(2016) Eric Krotkov et al.   Journal of Field Robotics

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Distributionally Robust Control of Constrained Stochastic Systems

(2015) Bart Van Parys et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Robots that can adapt like animals

(2015) Antoine Cully et al.   NATURE

Human-level control through deep reinforcement learning

(2015) Volodymyr Mnih et al.   NATURE

Reinforcement learning in robotics: A survey

(2013) Jens Kober et al.   INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

Simulation as an engine of physical scene understanding

(2013) P. W. Battaglia et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Approximate Bayesian Computation

(2013) Mikael Sunnåker et al.   PLoS Computational Biology

Lyapunov Stability and Strong Passivity Analysis for Nonlinear Descriptor Systems

(2012) Chunyu Yang et al.   IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS

The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics

(2012) Sylvain Koos et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation

(2012) Paul Fearnhead et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Bayesian robot system identification with input and output noise

(2010) Jo-Anne Ting et al.   NEURAL NETWORKS

Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems

(2010) Erick Delage et al.   OPERATIONS RESEARCH

Adaptive approximate Bayesian computation

(2009) M. A. Beaumont et al.   BIOMETRIKA

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Continuous Global Optimization in Multiview 3D Reconstruction

(2009) Kalin Kolev et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION