Ruben Grandia
- Biomedical Engineering top 10%
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Mechanical Engineering
- Aerospace Engineering top 10%
- Co-authors
- Marco HutterFarbod FarshidianFabian JeneltenLorenz WellhausenGiorgio ValsecchiHendrik KolvenbachMarko BjelonicTakahiro Miki
- Topics
- Robotic Locomotion and Control (15 papers)Prosthetics and Rehabilitation Robotics (9 papers)Robotic Path Planning Algorithms (6 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionBiomedical Engineering
- Journals
- ACM Transactions on GraphicsThe International Journal of Robotics ResearchIEEE Transactions on Robotics
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Ruben Grandia
19 papers receiving 661 citations
Hit Papers
Peers
Comparison fields: 5 of 63
- Biomedical Engineering 467
- Control and Systems Engineering 333
- Computer Vision and Pattern Recognition 223
- Mechanical Engineering 116
- Aerospace Engineering 100
Countries citing papers authored by Ruben Grandia
This map shows the geographic impact of Ruben Grandia'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 Ruben Grandia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruben Grandia more than expected).
Fields of papers citing papers by Ruben Grandia
This network shows the impact of papers produced by Ruben Grandia. 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 Ruben Grandia. The network helps show where Ruben Grandia may publish in the future.
Co-authorship network of co-authors of Ruben Grandia
This figure shows the co-authorship network connecting the top 25 collaborators of Ruben Grandia. A scholar is included among the top collaborators of Ruben Grandia 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 Ruben Grandia. Ruben Grandia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | Perceptive Locomotion Through Nonlinear Model-Predictive Controlbreakdown → | 123 |
| 6 | 9 | |
| 7 | 48 | |
| 8 | 64 | |
| 9 | 8 | |
| 10 | 45 | |
| 11 | 27 | |
| 12 | 54 | |
| 13 | 42 | |
| 14 | 34 | |
| 15 | 54 | |
| 16 | 67 | |
| 17 | 27 | |
| 18 | 6 | |
| 19 | 6 | |
| 20 | 23 |
About Ruben Grandia
Ruben Grandia is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 21 papers that have together received 691 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (15 papers), Prosthetics and Rehabilitation Robotics (9 papers) and Robotic Path Planning Algorithms (6 papers). The work is most often cited by research in Control and Systems Engineering (333 citations), Computer Vision and Pattern Recognition (223 citations) and Biomedical Engineering (467 citations). Ruben Grandia has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Marco Hutter, Farbod Farshidian, Fabian Jenelten, Lorenz Wellhausen, Giorgio Valsecchi, Hendrik Kolvenbach, Marko Bjelonic, Takahiro Miki, Timon Homberger and Samuel Zimmermann. Their work appears in journals such as ACM Transactions on Graphics, The International Journal of Robotics Research and IEEE Transactions on Robotics.
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.