Michael Lutter
Impact in
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- Robot Manipulation and Learning
- Fault Detection and Control Systems
- Robotic Mechanisms and Dynamics
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- Model Reduction and Neural Networks
Papers in
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- Robot Manipulation and Learning 4
- Real-time simulation and control systems 2
- Robotic Mechanisms and Dynamics 1
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- Reinforcement Learning in Robotics 4
- Co-authors
- Jan Peters (10 shared papers)Christian Ritter (1 shared paper)Marco Ewerton (2 shared papers)Dorothea Koert (2 shared papers)Debora Clever (3 shared papers)Dieter Fox (2 shared papers)Animesh Garg (2 shared papers)Kim D. Listmann (2 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)The International Journal of Robotics Research (1 paper)International Journal of Humanoid Robotics (1 paper)International Conference on Learning Representations (1 paper)arXiv (Cornell University) (1 paper)
In The Last Decade
Michael Lutter
9 papers receiving 96 citations
Peers
Comparison fields: 5 of 35
- Control and Systems Engineering 51
- Statistical and Nonlinear Physics 27
- Artificial Intelligence 33
- Industrial and Manufacturing Engineering 10
- Mechanical Engineering 23
Countries citing papers authored by Michael Lutter
This map shows the geographic impact of Michael Lutter's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Lutter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Lutter more than expected).
Fields of papers citing papers by Michael Lutter
This network shows the impact of papers produced by Michael Lutter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Lutter. The network helps show where Michael Lutter may publish in the future.
Co-authors
The 10 scholars most cited alongside Michael Lutter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 43 | |
| 2 | 2023 | 26 | |
| 3 | 2018 | 11 | |
| 4 | 2022 | 5 | |
| 5 | 2021 | 4 | |
| 6 | 2019 | 4 | |
| 7 | 2021 | 3 | |
| 8 | HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints. | 2019 | 1 |
| 9 | Value Iteration in Continuous Actions, States and Time | 2021 | 1 |
| 10 | Differential Equations as a Model Prior for Deep Learning and its Applications in Robotics | 2020 | 0 |
About Michael Lutter
Michael Lutter is a scholar working on Control and Systems Engineering, Artificial Intelligence, Social Psychology, Statistical and Nonlinear Physics and Biomedical Engineering, having authored 10 papers that have together received 98 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Robot Manipulation and Learning (4 papers), Prosthetics and Rehabilitation Robotics (2 papers), Social Robot Interaction and HRI (2 papers), Model Reduction and Neural Networks (2 papers), Real-time simulation and control systems (2 papers), Adaptive Dynamic Programming Control (1 paper) and Robotic Mechanisms and Dynamics (1 paper). The work is most often cited by research in Control and Systems Engineering (51 citations), Statistical and Nonlinear Physics (27 citations), Artificial Intelligence (33 citations), Industrial and Manufacturing Engineering (10 citations) and Mechanical Engineering (23 citations). Michael Lutter has collaborated with scholars based in Germany, Israel and Canada. Frequent co-authors include Jan Peters, Christian Ritter, Marco Ewerton, Dorothea Koert, Debora Clever, Dieter Fox, Animesh Garg, Kim D. Listmann, Stephan Rinderknecht and Shie Mannor. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The International Journal of Robotics Research, International Journal of Humanoid Robotics, International Conference on Learning Representations and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.