Andreas ten Pas
Impact in
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- Robot Manipulation and Learning
- Cognitive Neuroscience top 10%
- Tactile and Sensory Interactions
Papers in
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- Robot Manipulation and Learning 7
- Robotic Mechanisms and Dynamics 2
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- Soft Robotics and Applications 4
- Co-authors
- Robert W. Platt (6 shared papers)Wenzhen Yuan (1 shared paper)Edward H. Adelson (1 shared paper)Mandayam A. Srinivasan (1 shared paper)Kate Saenko (1 shared paper)Christopher Amato (1 shared paper)Stefano Panzieri (1 shared paper)Holly A. Yanco (1 shared paper)
- Journals
- 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Andreas ten Pas
8 papers receiving 264 citations
Peers
Comparison fields: 5 of 31
- Control and Systems Engineering 178
- Cognitive Neuroscience 129
- Human-Computer Interaction 33
- Biomedical Engineering 172
- Computer Vision and Pattern Recognition 55
Countries citing papers authored by Andreas ten Pas
This map shows the geographic impact of Andreas ten Pas'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 Andreas ten Pas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas ten Pas more than expected).
Fields of papers citing papers by Andreas ten Pas
This network shows the impact of papers produced by Andreas ten Pas. 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 Andreas ten Pas. The network helps show where Andreas ten Pas may publish in the future.
Co-authors
The 8 scholars most cited alongside Andreas ten Pas, 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 | 2014 | 167 | |
| 2 | Learning a visuomotor controller for real world robotic grasping using simulated depth images | 2017 | 50 |
| 3 | 2019 | 43 | |
| 4 | 2015 | 11 | |
| 5 | 2021 | 4 | |
| 6 | Localizing antipodal grasps in point clouds. | 2015 | 4 |
| 7 | Category Level Pick and Place Using Deep Reinforcement Learning. | 2017 | 4 |
| 8 | A Scooter-Mounted Robot Arm to Assist with Activities of Daily Life. | 2018 | 2 |
About Andreas ten Pas
Andreas ten Pas is a scholar working on Control and Systems Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Mechanical Engineering, having authored 8 papers that have together received 285 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (7 papers), Soft Robotics and Applications (4 papers), Robotic Mechanisms and Dynamics (2 papers), Modular Robots and Swarm Intelligence (2 papers), Hand Gesture Recognition Systems (2 papers), Reinforcement Learning in Robotics (2 papers), Robotic Path Planning Algorithms (2 papers) and Social Robot Interaction and HRI (1 paper). The work is most often cited by research in Control and Systems Engineering (178 citations), Cognitive Neuroscience (129 citations), Human-Computer Interaction (33 citations), Biomedical Engineering (172 citations) and Computer Vision and Pattern Recognition (55 citations). Andreas ten Pas has collaborated with scholars based in United States and India. Frequent co-authors include Robert W. Platt, Wenzhen Yuan, Edward H. Adelson, Mandayam A. Srinivasan, Kate Saenko, Christopher Amato, Stefano Panzieri and Holly A. Yanco. Their work appears in journals such as 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 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.