Manuel Mühlig
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Social Psychology
- Co-authors
- Michael GiengerJochen J. SteilChristian GoerickKarola PitschAnna-Lisa VollmerNick HawesBruno LacerdaTakahide Yoshiike
- Topics
- Robot Manipulation and Learning (12 papers)Reinforcement Learning in Robotics (7 papers)Robotic Locomotion and Control (5 papers)
- Partner nations
- GermanyUnited KingdomJapan
In The Last Decade
Manuel Mühlig
17 papers receiving 264 citations
Peers
Comparison fields: 5 of 39
- Control and Systems Engineering 191
- Artificial Intelligence 123
- Computer Vision and Pattern Recognition 78
- Biomedical Engineering 57
- Social Psychology 44
Countries citing papers authored by Manuel Mühlig
This map shows the geographic impact of Manuel Mühlig'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 Manuel Mühlig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuel Mühlig more than expected).
Fields of papers citing papers by Manuel Mühlig
This network shows the impact of papers produced by Manuel Mühlig. 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 Manuel Mühlig. The network helps show where Manuel Mühlig may publish in the future.
Co-authorship network of co-authors of Manuel Mühlig
This figure shows the co-authorship network connecting the top 25 collaborators of Manuel Mühlig. A scholar is included among the top collaborators of Manuel Mühlig based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Manuel Mühlig. Manuel Mühlig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 14 | |
| 3 | 0 | |
| 4 | 9 | |
| 5 | 1 | |
| 6 | SmartLobby: A 24/7 Human-Machine-Interaction Space within an Office Environment. | 0 |
| 7 | 1 | |
| 8 | 29 | |
| 9 | 2 | |
| 10 | 23 | |
| 11 | A Dynamical Systems Approach to Adaptive Sequencing of Movement Primitives | 5 |
| 12 | 13 | |
| 13 | 48 | |
| 14 | 2 | |
| 15 | 15 | |
| 16 | 10 | |
| 17 | 8 | |
| 18 | 58 | |
| 19 | 34 |
About Manuel Mühlig
Manuel Mühlig is a scholar working on Control and Systems Engineering, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 274 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (12 papers), Reinforcement Learning in Robotics (7 papers) and Robotic Locomotion and Control (5 papers). The work is most often cited by research in Control and Systems Engineering (191 citations), Human-Computer Interaction (26 citations) and Artificial Intelligence (123 citations). Manuel Mühlig has collaborated with scholars based in Germany, United Kingdom and Japan. Frequent co-authors include Michael Gienger, Jochen J. Steil, Christian Goerick, Karola Pitsch, Anna-Lisa Vollmer, Nick Hawes, Bruno Lacerda, Takahide Yoshiike, Tobias Luksch and Britta Wrede. Their work appears in journals such as PLoS ONE, IEEE Transactions on Robotics and Autonomous Robots.
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.