Peters, Jan

Reinforcement learning in robotics: A survey

Kober, J., Bagnell, J. A., & Peters, J. (2013) · The International Journal of Robotics Research

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 3,160

Reinforcement learning of motor skills with policy gradients

Peters, J., & Schaal, S. (2008) · Neural Networks

Reinforcement Learning in RoboticsMotor Control and Adaptation

Cited by 831

Natural Actor-Critic

Peters, J., & Schaal, S. (2008) · Neurocomputing

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 738

Model learning for robot control: A survey

Nguyen-Tuong, D., & Peters, J. (2011) · Cognitive Processing

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 503

An algorithmic perspective on imitation learning

Osa, T., Pajarinen, J., Neumann, G., Bagnell, J. A., Abbeel, P., & Peters, J. (2018) · Foundations and Trends in Robotics

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 405

Probabilistic movement modeling for intention inference in human–robot interaction

Wang, Z., Mülling, K., Deisenroth, M. P., Ben Amor, H., Vogt, D., Schölkopf, B., & Peters, J. (2013) · The International Journal of Robotics Research

Social Robot Interaction and HRIAction Observation and Synchronization

Cited by 171

Learning to Control in Operational Space

Peters, J., & Schaal, S. (2008) · The International Journal of Robotics Research

Reinforcement Learning in RoboticsRobotic Mechanisms and Dynamics

Cited by 162

Sim2Real in Robotics and Automation: Applications and Challenges

Hofer, S., Bekris, K., Handa, A., Gamboa, J. C., Mozifian, M., Golemo, F., Atkeson, C., Fox, D., Goldberg, K., Leonard, J., et al. (2021) · IEEE Transactions on Automation Science and Engineering

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 154

Movement templates for learning of hitting and batting

Kober, J., Mülling, K., Krömer, O., Lampert, C. H., Schölkopf, B., & Peters, J. (2010) · 2010 IEEE International Conference on Robotics and Automation

Motor Control and AdaptationReinforcement Learning in Robotics

Cited by 152

Robot Learning From Randomized Simulations: A Review

Muratore, F., Ramos, F., Turk, G., Yu, W., Gienger, M., & Peters, J. (2022) · Frontiers in Robotics and AI

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 128

Trajectory planning for optimal robot catching in real-time

Lampariello, R., Nguyen-Tuong, D., Castellini, C., Hirzinger, G., & Peters, J. (2011) · 2011 IEEE International Conference on Robotics and Automation

Robotic Path Planning AlgorithmsRobotic Mechanisms and Dynamics

Cited by 117

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Embodiment Collaboration, O'Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 111

Data-Efficient Generalization of Robot Skills with Contextual Policy Search

Kupcsik, A., Deisenroth, M., Peters, J., & Neumann, G. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 92

Learning grasp affordance densities

Detry, R., Kraft, D., Kroemer, O., Bodenhagen, L., Peters, J., Krüger, N., & Piater, J. (2011) · Paladyn Journal of Behavioral Robotics

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 79

ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows

Urain, J., Ginesi, M., Tateo, D., & Peters, J. (2020) · 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Reinforcement Learning in RoboticsGaussian Processes and Bayesian Inference

Cited by 56

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

Parmas, P., Rasmussen, C. E., Peters, J., & Doya, K. (2019) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 34

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

Parmas, P., Rasmussen, C. E., Peters, J., & Doya, K. (2018) · Apollo - University of Cambridge Repository

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 32

Directed Acyclic Graph Neural Network for Human Motion Prediction

Li, Q., Chalvatzaki, G., Peters, J., & Wang, Y. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Human Motion and AnimationHuman Pose and Action Recognition

Cited by 29

Building a Library of Tactile Skills Based on FingerVision

Belousov, B., Sadybakasov, A., Wibranek, B., Veiga, F., Tessmann, O., & Peters, J. (2019) · 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)

Robot Manipulation and LearningTeleoperation and Haptic Systems

Cited by 16

One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion

Bohlinger, N., Czechmanowski, G., Krupka, M., Kicki, P., Walas, K., Peters, J., & Tateo, D. (2024) · arXiv

Robotic Locomotion and ControlReinforcement Learning in Robotics

Cited by 4