Lorenzo Sabattini

146 papers receiving 2.7k citations

Hit Papers

Proceedings of the 18th International Conference on Auton...2019202620212023201950100150200250

Peers

Lorenzo Sabattini
Comparison fields: 5 of 118
  • Computer Networks and Communications 1.1k
  • Control and Systems Engineering 688
  • Computer Vision and Pattern Recognition 628
  • Mechanical Engineering 627
  • Industrial and Manufacturing Engineering 522
Replace Jun Ota with:
Jun Ota Japan
B. Benhabib Canada
Weihua Sheng United States
Quan Liu China
Yingzi Lin United States
Cristian Secchi Italy
Luca Iocchi Italy
Nilanjan Chakraborty United States
Nathan Koenig United States
Chao Huang China
Lorenzo Sabattini relative to Jun Ota Japan Jun Ota's profile →
Citations per field
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Jun Ota · 1×
Citations per year

Countries citing papers authored by Lorenzo Sabattini

Since Specialization
Citations

This map shows the geographic impact of Lorenzo Sabattini'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 Lorenzo Sabattini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lorenzo Sabattini more than expected).

Fields of papers citing papers by Lorenzo Sabattini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lorenzo Sabattini. 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 Lorenzo Sabattini. The network helps show where Lorenzo Sabattini may publish in the future.

Co-authorship network of co-authors of Lorenzo Sabattini

This figure shows the co-authorship network connecting the top 25 collaborators of Lorenzo Sabattini. A scholar is included among the top collaborators of Lorenzo Sabattini 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 Lorenzo Sabattini. Lorenzo Sabattini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Preservation of Giant Component Size after Robot Failure for Robustness of Multi-Robot Network
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Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systemsbreakdown →
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About Lorenzo Sabattini

Lorenzo Sabattini is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Control and Systems Engineering, having authored 156 papers that have together received 2.7k indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (60 papers), Modular Robots and Swarm Intelligence (32 papers) and Robotic Path Planning Algorithms (29 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (522 citations), Computer Networks and Communications (1.1k citations) and Computer Vision and Pattern Recognition (628 citations). Lorenzo Sabattini has collaborated with scholars based in Italy, United States and Brazil. Frequent co-authors include Cristian Secchi, Cesare Fantuzzi, Nikhil Chopra, Valerio Digani, Valeria Villani, Damjan Miklić, Jen Jen Chung, Roland Siegwart, Kagan Tumer and Andrea Gasparri. Their work appears in journals such as Nature Communications, Journal of Neurology Neurosurgery & Psychiatry and IEEE Access.

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.

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