Arunkumar Byravan
Impact in
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- Robotic Path Planning Algorithms
- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
- Robotic Mechanisms and Dynamics
Papers in
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- Advanced Vision and Imaging 3
- Human Pose and Action Recognition 3
- Robotic Path Planning Algorithms 2
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- Robot Manipulation and Learning 5
- Co-authors
- Dieter Fox (5 shared papers)Byron Boots (2 shared papers)Siddhartha S Srinivasa (1 shared paper)Franziska Meier (1 shared paper)Benjamin M. Moran (1 shared paper)Leonard Hasenclever (1 shared paper)Fereshteh Sadeghi (1 shared paper)Tuomas Haarnoja (2 shared papers)
- Journals
- Science Robotics (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Arunkumar Byravan
9 papers receiving 231 citations
Arunkumar Byravan's Hit Papers
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 111
- Control and Systems Engineering 87
- Computer Graphics and Computer-Aided Design 11
- Artificial Intelligence 81
- Aerospace Engineering 37
Countries citing papers authored by Arunkumar Byravan
This map shows the geographic impact of Arunkumar Byravan'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 Arunkumar Byravan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arunkumar Byravan more than expected).
Fields of papers citing papers by Arunkumar Byravan
This network shows the impact of papers produced by Arunkumar Byravan. 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 Arunkumar Byravan. The network helps show where Arunkumar Byravan may publish in the future.
Co-authors
The 25 scholars most cited alongside Arunkumar Byravan, 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 | Learning agile soccer skills for a bipedal robot with deep reinforcement learning Hit paper breakdown → | 2024 | 108 |
| 2 | 2023 | 36 | |
| 3 | 2014 | 29 | |
| 4 | 2018 | 29 | |
| 5 | 2014 | 18 | |
| 6 | 2017 | 11 | |
| 7 | 2019 | 5 | |
| 8 | Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion | 2021 | 3 |
| 9 | 2021 | 3 |
About Arunkumar Byravan
Arunkumar Byravan is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Biophysics and Biomedical Engineering, having authored 9 papers that have together received 242 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Advanced Vision and Imaging (3 papers), Reinforcement Learning in Robotics (3 papers), Human Pose and Action Recognition (3 papers), Robotic Path Planning Algorithms (2 papers), Robotic Locomotion and Control (2 papers), Cell Image Analysis Techniques (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (111 citations), Control and Systems Engineering (87 citations), Computer Graphics and Computer-Aided Design (11 citations), Artificial Intelligence (81 citations) and Aerospace Engineering (37 citations). Arunkumar Byravan has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Dieter Fox, Byron Boots, Siddhartha S Srinivasa, Franziska Meier, Benjamin M. Moran, Leonard Hasenclever, Fereshteh Sadeghi, Tuomas Haarnoja, Jan Humplik and Francesco Nori. Their work appears in journals such as Science Robotics 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.