Pedro J. Sanz
- Ocean Engineering top 0.2%
- Control and Systems Engineering top 1%
- Computer Vision and Pattern Recognition top 1%
- Aerospace Engineering top 2%
- Mechanical Engineering top 5%
- Co-authors
- R. Marı́nÁngel P. del PobilMario PratsPere RidaoJ. FernándezGabriel OliverDavid RibasJavier Pérez
- Topics
- Underwater Vehicles and Communication Systems (60 papers)Robot Manipulation and Learning (42 papers)Robotics and Sensor-Based Localization (39 papers)
In The Last Decade
Pedro J. Sanz
143 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 97
- Ocean Engineering 1.0k
- Control and Systems Engineering 940
- Computer Vision and Pattern Recognition 857
- Aerospace Engineering 663
- Mechanical Engineering 624
Countries citing papers authored by Pedro J. Sanz
This map shows the geographic impact of Pedro J. Sanz'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 Pedro J. Sanz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro J. Sanz more than expected).
Fields of papers citing papers by Pedro J. Sanz
This network shows the impact of papers produced by Pedro J. Sanz. 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 Pedro J. Sanz. The network helps show where Pedro J. Sanz may publish in the future.
Co-authorship network of co-authors of Pedro J. Sanz
This figure shows the co-authorship network connecting the top 25 collaborators of Pedro J. Sanz. A scholar is included among the top collaborators of Pedro J. Sanz 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 Pedro J. Sanz. Pedro J. Sanz 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 | 14 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 8 | |
| 9 | 9 | |
| 10 | 40 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | Grasper HIL simulation towards autonomous manipulation of an underwater panel in a permanent observatory | 6 |
| 14 | 35 | |
| 15 | User interface oriented to the specification of underwater robotic interventions | 2 |
| 16 | Recent progress in the RAUVI project: A Reconfigurable autonomous underwater vehicle for intervention | 23 |
| 17 | 7 | |
| 18 | The Human-Machine Interaction through the UJI Telerobotic Training System. | 2 |
| 19 | 1 | |
| 20 | An Undergraduate Robotics Course Via Web. | 3 |
About Pedro J. Sanz
Pedro J. Sanz is a scholar working on Ocean Engineering, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 148 papers that have together received 2.4k indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (60 papers), Robot Manipulation and Learning (42 papers) and Robotics and Sensor-Based Localization (39 papers). The work is most often cited by research in Ocean Engineering (1.0k citations), Computer Vision and Pattern Recognition (857 citations) and Control and Systems Engineering (940 citations). Pedro J. Sanz has collaborated with scholars based in Spain, Italy and Portugal. Frequent co-authors include R. Marı́n, Ángel P. del Pobil, Mario Prats, Pere Ridao, J. Fernández, Gabriel Oliver, David Ribas, Javier Pérez, J.C. García and Antonio Morales. Their work appears in journals such as IEEE Transactions on Industrial Electronics, IEEE Access and Sensors.
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.