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Michael Lutter
Michael Lutter
Boston Dynamics
Verified email at bostondynamics.com - Homepage
Title
Cited by
Cited by
Year
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
M Lutter, C Ritter, J Peters
International Conference on Learning Representations (ICLR), 2019
2432019
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems
M Lutter, K Listmann, J Peters
International Conference on Intelligent Robots and Systems (IROS), 2019
362019
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning
M Lutter, J Silberbauer, J Watson, J Peters
International Conference on Robotics and Automation (ICRA), 2021
202021
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints
M Lutter, B Belousov, K Listmann, D Clever, J Peters
Conference on Robot Learning (CoRL), 2019
152019
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards
K Ploeger, M Lutter, J Peters
Conference on Robot Learning (CoRL), 2020
132020
Online learning of an open-ended skill library for collaborative tasks
D Koert, S Trick, M Ewerton, M Lutter, J Peters
2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 1-9, 2018
132018
Value Iteration in Continuous Actions, States and Time
M Lutter, S Mannor, J Peters, D Fox, A Garg
International Conference on Machone Learning (ICML), 2021
112021
Robust Value Iteration for Continuous Control Tasks
M Lutter, S Mannor, J Peters, D Fox, A Garg
Robotics: Science and Systems (RSS), 2021
102021
A Differentiable Newton Euler Algorithm for Multi-body Model Learning
M Lutter, J Silberbauer, J Watson, J Peters
ICML Workshop on Inductive Biases, Invariances and Generalization in RL, 2020
92020
Learning dynamics models for model predictive agents
M Lutter, L Hasenclever, A Byravan, G Dulac-Arnold, P Trochim, N Heess, ...
arXiv preprint arXiv:2109.14311, 2021
72021
Combining physics and deep learning to learn continuous-time dynamics models
M Lutter, J Peters
arXiv preprint arXiv:2110.01894, 2021
52021
Incremental learning of an open-ended collaborative skill library
D Koert, S Trick, M Ewerton, M Lutter, J Peters
International Journal of Humanoid Robotics 17 (01), 2050001, 2020
42020
A Differentiable Newton-Euler Algorithm for Real-World Robotics
M Lutter, J Silberbauer, J Watson, J Peters
arXiv preprint arXiv:2110.12422, 2021
32021
Continuous-Time Fitted Value Iteration for Robust Policies
M Lutter, B Belousov, S Mannor, D Fox, A Garg, J Peters
arXiv preprint arXiv:2110.01954, 2021
12021
Building Skill Learning Systems for Robotics
M Lutter, D Clever, R Kirsten, K Listmann, J Peters
2021 IEEE 17th International Conference on Automation Science and …, 2021
12021
Trajectory optimization of energy consumption and expected service life of a robotic system
F Stuhlenmiller, D Clever, S Rinderknecht, M Lutter, J Peters
2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2021
12021
Evaluating the Robustness of HJB Optimal Feedback Control
M Lutter, D Clever, B Belousov, K Listmann, J Peters
ISR 2020; 52th International Symposium on Robotics, 1-8, 2020
12020
Differential Equations as a Model Prior for Deep Learning and its Applications in Robotics
M Lutter, J Peters
ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020
12020
Revisiting Model-based Value Expansion
D Palenicek, M Lutter, J Peters
arXiv preprint arXiv:2203.14660, 2022
2022
Inductive Biases in Machine Learning for Robotics and Control
M Lutter
Technische Universität, 2021
2021
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