Marius Wiggert
Impact in
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- Robotic Path Planning Algorithms
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- Reinforcement Learning in Robotics
Papers in
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- Reinforcement Learning in Robotics 2
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- Distributed Control Multi-Agent Systems 2
- Energy Efficient Wireless Sensor Networks 1
- Co-authors
- Claire J. Tomlin (6 shared papers)Anca D. Dragan (2 shared papers)Pierre F. J. Lermusiaux (3 shared papers)Stefano Carpin (1 shared paper)Joshua H. Viers (1 shared paper)Stavros Vougioukas (1 shared paper)Ken Goldberg (1 shared paper)Ron Berenstein (1 shared paper)
- Journals
- The International Journal of Robotics Research (1 paper)2022 IEEE 61st Conference on Decision and Control (CDC) (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Marius Wiggert
7 papers receiving 37 citations
Peers
Comparison fields: 5 of 23
- Computer Vision and Pattern Recognition 11
- Artificial Intelligence 17
- Control and Systems Engineering 10
- Ocean Engineering 6
- Aquatic Science 2
Countries citing papers authored by Marius Wiggert
This map shows the geographic impact of Marius Wiggert'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 Marius Wiggert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marius Wiggert more than expected).
Fields of papers citing papers by Marius Wiggert
This network shows the impact of papers produced by Marius Wiggert. 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 Marius Wiggert. The network helps show where Marius Wiggert may publish in the future.
Co-authors
The 8 scholars most cited alongside Marius Wiggert, 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 | 2022 | 16 | |
| 2 | 2019 | 7 | |
| 3 | 2022 | 5 | |
| 4 | 2022 | 4 | |
| 5 | 2020 | 2 | |
| 6 | 2023 | 2 | |
| 7 | 2024 | 1 |
About Marius Wiggert
Marius Wiggert is a scholar working on Artificial Intelligence, Computer Networks and Communications, Ocean Engineering, Cognitive Neuroscience and Social Psychology, having authored 7 papers that have together received 37 indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (2 papers), Reinforcement Learning in Robotics (2 papers), Distributed Control Multi-Agent Systems (2 papers), EEG and Brain-Computer Interfaces (2 papers), Plant Water Relations and Carbon Dynamics (1 paper), Energy Efficient Wireless Sensor Networks (1 paper), Structural Integrity and Reliability Analysis (1 paper) and Human-Automation Interaction and Safety (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (11 citations), Artificial Intelligence (17 citations), Control and Systems Engineering (10 citations), Ocean Engineering (6 citations) and Aquatic Science (2 citations). Marius Wiggert has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Claire J. Tomlin, Anca D. Dragan, Pierre F. J. Lermusiaux, Stefano Carpin, Joshua H. Viers, Stavros Vougioukas, Ken Goldberg and Ron Berenstein. Their work appears in journals such as The International Journal of Robotics Research, 2022 IEEE 61st Conference on Decision and Control (CDC) 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.