Start Up Reading Package

The following list of papers should serve as a starting point if you want to get into a specific topic. Keep in mind that these lists are by far not complete. There is plenty of research that you will discover over time. In case you encounter a paper that you consider worthy to be on this list, feel free to add it.

Robotics & Robot learning

Kober et al., " Reinforcement Learning in Robotics: A Survey", International Journal of Robotics Research, 2013

Deisenroth et al., "A Survey on Policy Search for Robotics", Foundations and Trends in Robotics, 2013

Kuindersma et al., "Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot", Autonomous Robots, 2016

Kroemer et al., "A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms", Journal of Machine Learning Research, 2019

Reinforcement Learning

Mohamed et al., "Monte Carlo Gradient Estimation in Machine Learning", Journal of Machine Learning Research, 2020

Sutton and Barto, "Reinforcement Learning: An Introduction", 2nd edition, 2020

Agarwal et al., "Reinforcement Learning: Theory and Algorithms", draft, 2021

Machine Learning

Bishop, "Pattern Recognition and Machine Learning", 5th edition, 2007

Stulp and Sigaud, "Many Regression Algorithms, One Unified Model: A Review", Neural Networks, 2015

Bach, "Learning Theory from First Principles", draft, 2021

Model Learning

Nguyen-Tuong and Peters, "Model Learning in Robotics: a Survey", Cognitive Processing, 2011

Motion Planning & Trajectory Optimization

Ratliff et al., "Gradient optimization techniques for efficient motion planning", International Conference on Robotics and Automation, 2009

Kalakrishnan et al., "Stochastic trajectory optimization for motion planning", International Conference on Robotics and Automation, 2011

Williams et al., "Model predictive path integral control using covariance variable importance sampling", arXiv, 2015

Imitation Learning

Takayuki et al., "An Algorithmic Perspective on Imitation Learning", Foundations and Trends in Robotics, 2018

Sim-to-Real & Domain Randomization

Muratore et al., "Robot Learning from Randomized Simulations: A Review", Frontiers in Robotics and AI, 2021

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