David Hoeller
Impact in
-
- Robotic Path Planning Algorithms
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
- Software 2
- Software Testing and Debugging Techniques 2
-
- Robotic Path Planning Algorithms 4
- Co-authors
- Marco HutterNikita RudinAnimesh GargMayank MittalMarko BjelonicFarbod FarshidianShehryar KhattakB. N. Babich
- Journals
- IEEE Robotics and Automation Letters (2 papers)Science Robotics (1 paper)IFAC-PapersOnLine (1 paper)arXiv (Cornell University) (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (3 papers)
- Partner nations
- SwitzerlandUnited StatesCanada
In The Last Decade
David Hoeller
12 papers receiving 408 citations
Hit Papers
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 160
- Control and Systems Engineering 143
- Biomedical Engineering 183
- Aerospace Engineering 95
- Artificial Intelligence 93
Countries citing papers authored by David Hoeller
This map shows the geographic impact of David Hoeller'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 David Hoeller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Hoeller more than expected).
Fields of papers citing papers by David Hoeller
This network shows the impact of papers produced by David Hoeller. 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 David Hoeller. The network helps show where David Hoeller may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Hoeller, 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 | 2024 | 9 | |
| 2 | ANYmal parkour: Learning agile navigation for quadrupedal robots Hit paper breakdown → | 2024 | 98 |
| 3 | Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments Hit paper breakdown → | 2023 | 89 |
| 4 | 2022 | 49 | |
| 5 | 2022 | 50 | |
| 6 | 2022 | 21 | |
| 7 | 2022 | 39 | |
| 8 | 2021 | 34 | |
| 9 | Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion | 2020 | 6 |
| 10 | 2020 | 8 | |
| 11 | 2020 | 5 | |
| 12 | 2017 | 18 |
About David Hoeller
David Hoeller is a scholar working on Software, Computer Vision and Pattern Recognition, Control and Systems Engineering, Aerospace Engineering and Biomedical Engineering, having authored 12 papers that have together received 426 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (7 papers), Robotic Path Planning Algorithms (4 papers), Robotics and Sensor-Based Localization (3 papers), Reinforcement Learning in Robotics (3 papers), Advanced Control Systems Optimization (2 papers), Fault Detection and Control Systems (2 papers), Robot Manipulation and Learning (2 papers) and Software Testing and Debugging Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Control and Systems Engineering (143 citations), Biomedical Engineering (183 citations), Aerospace Engineering (95 citations) and Artificial Intelligence (93 citations). David Hoeller has collaborated with scholars based in Switzerland, United States and Canada. Frequent co-authors include Marco Hutter, Nikita Rudin, Animesh Garg, Mayank Mittal, Marko Bjelonic, Farbod Farshidian, Shehryar Khattak, B. N. Babich, Calvin Yu and Jingzhou Liu. Their work appears in journals such as IEEE Robotics and Automation Letters, Science Robotics, IFAC-PapersOnLine, arXiv (Cornell University) and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.