S. Sekhavat
- Computer Vision and Pattern Recognition top 2%
- Control and Systems Engineering top 2%
- Aerospace Engineering top 5%
- Automotive Engineering top 5%
- Biomedical Engineering
- Co-authors
- Jean‐Paul LaumondF. LargeZvi ShillerFlorent LamirauxJ.-P. LaumondCédric PradalierMark H. OvermarsP. Švestka
- Topics
- Robotic Path Planning Algorithms (23 papers)Control and Dynamics of Mobile Robots (17 papers)Vehicle Dynamics and Control Systems (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringAutomotive Engineering
- Journals
- The International Journal of Robotics ResearchIEEE Transactions on Robotics and AutomationAdvanced Robotics
- Partner nations
- FranceUnited StatesNetherlands
In The Last Decade
S. Sekhavat
25 papers receiving 548 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 535
- Control and Systems Engineering 396
- Aerospace Engineering 226
- Automotive Engineering 142
- Biomedical Engineering 113
Countries citing papers authored by S. Sekhavat
This map shows the geographic impact of S. Sekhavat'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 S. Sekhavat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Sekhavat more than expected).
Fields of papers citing papers by S. Sekhavat
This network shows the impact of papers produced by S. Sekhavat. 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 S. Sekhavat. The network helps show where S. Sekhavat may publish in the future.
Co-authorship network of co-authors of S. Sekhavat
This figure shows the co-authorship network connecting the top 25 collaborators of S. Sekhavat. A scholar is included among the top collaborators of S. Sekhavat 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 S. Sekhavat. S. Sekhavat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 22 | |
| 3 | 19 | |
| 4 | Experimental Issues from Map Building to Trajectory Execution for a Bi-steerable Car. | 2 |
| 5 | 14 | |
| 6 | 12 | |
| 7 | 4 | |
| 8 | 23 | |
| 9 | 3 | |
| 10 | 7 | |
| 11 | 28 | |
| 12 | 17 | |
| 13 | 111 | |
| 14 | Motion planning for a Bi-steerable Car. | 7 |
| 15 | 8 | |
| 16 | 5 | |
| 17 | 96 | |
| 18 | 68 | |
| 19 | 90 | |
| 20 | 11 |
About S. Sekhavat
S. Sekhavat is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Control and Systems Engineering, having authored 26 papers that have together received 624 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (23 papers), Control and Dynamics of Mobile Robots (17 papers) and Vehicle Dynamics and Control Systems (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (535 citations), Control and Systems Engineering (396 citations) and Automotive Engineering (142 citations). S. Sekhavat has collaborated with scholars based in France, United States and Netherlands. Frequent co-authors include Jean‐Paul Laumond, F. Large, Zvi Shiller, Florent Lamiraux, J.-P. Laumond, Cédric Pradalier, Mark H. Overmars, P. Švestka, Monique Chyba and C. Laugier. Their work appears in journals such as The International Journal of Robotics Research, IEEE Transactions on Robotics and Automation and Advanced 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.