Rosen Diankov
- Control and Systems Engineering top 1%
- Computer Vision and Pattern Recognition top 2%
- Biomedical Engineering top 10%
- Aerospace Engineering top 5%
- Artificial Intelligence top 5%
- Co-authors
- James KuffnerTakeo KanadeDave FergusonSiddhartha S SrinivasaDmitry BerensonSatoshi KagamiKoichi NishiwakiCasey J. Helfrich
- Topics
- Robot Manipulation and Learning (10 papers)Robotic Path Planning Algorithms (7 papers)Robotics and Sensor-Based Localization (4 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- Proceedings of the IEEEAutonomous RobotsFigshare
- Partner nations
- United StatesJapanGermany
In The Last Decade
Rosen Diankov
13 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Control and Systems Engineering 873
- Computer Vision and Pattern Recognition 611
- Biomedical Engineering 376
- Aerospace Engineering 243
- Artificial Intelligence 229
Countries citing papers authored by Rosen Diankov
This map shows the geographic impact of Rosen Diankov'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 Rosen Diankov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rosen Diankov more than expected).
Fields of papers citing papers by Rosen Diankov
This network shows the impact of papers produced by Rosen Diankov. 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 Rosen Diankov. The network helps show where Rosen Diankov may publish in the future.
Co-authorship network of co-authors of Rosen Diankov
This figure shows the co-authorship network connecting the top 25 collaborators of Rosen Diankov. A scholar is included among the top collaborators of Rosen Diankov 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 Rosen Diankov. Rosen Diankov 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 | Automated construction of robotic manipulation programsbreakdown → | 293 |
| 3 | 2 | |
| 4 | 216 | |
| 5 | 34 | |
| 6 | 15 | |
| 7 | 87 | |
| 8 | OpenRAVE: A Planning Architecture for Autonomous Robotics | 262 |
| 9 | 69 | |
| 10 | 130 | |
| 11 | 2 | |
| 12 | 47 | |
| 13 | The Effects of Fully Immersive Virtual Reality on the Learning of Physical Tasks | 43 |
About Rosen Diankov
Rosen Diankov is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (10 papers), Robotic Path Planning Algorithms (7 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Control and Systems Engineering (873 citations), Computer Vision and Pattern Recognition (611 citations) and Human-Computer Interaction (97 citations). Rosen Diankov has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include James Kuffner, Takeo Kanade, Dave Ferguson, Siddhartha S Srinivasa, Dmitry Berenson, Satoshi Kagami, Koichi Nishiwaki, Casey J. Helfrich, Geoffrey A. Hollinger and Garratt Gallagher. Their work appears in journals such as Proceedings of the IEEE, Autonomous Robots and Figshare.
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.