Jan Faigl

3.6k citations
168 papers · 2.8k · h-index 29

Impact in

Papers in

Jan Faigl

162 papers receiving 2.7k citations

Peers

Jan Faigl
Comparison fields: 5 of 110
  • Computer Vision and Pattern Recognition 1.6k
  • Aerospace Engineering 1.4k
  • Industrial and Manufacturing Engineering 378
  • Computer Networks and Communications 588
  • Control and Systems Engineering 427
Replace Stefano Carpin with:
Stefano Carpin United States
Anthony Stentz United States
A. Howard United States
P. B. Sujit India
Libor Přeučil Czechia
Ioan A. Şucan United States
Geoffrey A. Hollinger United States
Martin Saska Czechia
Dezhen Song United States
Fei Gao China
Jan Faigl relative to Stefano Carpin United States Stefano Carpin's profile →
Citations per field
00.5×1.5×2.1×
Stefano Carpin · 1×
Citations per year

Countries citing papers authored by Jan Faigl

Since Specialization
Citations

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

Fields of papers citing papers by Jan Faigl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Faigl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Faigl Line = papers co-authored together Jan Faigl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 168 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011221
2 2014175
3 2016111
4 202098
5 201375
6 200971
7 201769
8 201764
9 201061
10 201960
11 201256
12 201749
13 201248
14 201845
15 201141
16 202138
17 201038
18 201337
19 201936
20 201835

About Jan Faigl

Jan Faigl is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Biomedical Engineering, Industrial and Manufacturing Engineering and Control and Systems Engineering, having authored 168 papers that have together received 2.8k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (91 papers), Robotics and Sensor-Based Localization (59 papers), Robotic Locomotion and Control (35 papers), Vehicle Routing Optimization Methods (30 papers), Modular Robots and Swarm Intelligence (21 papers), Robot Manipulation and Learning (15 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Autonomous Vehicle Technology and Safety (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Aerospace Engineering (1.4k citations), Industrial and Manufacturing Engineering (378 citations), Computer Networks and Communications (588 citations) and Control and Systems Engineering (427 citations). Jan Faigl has collaborated with scholars based in Czechia, United States and United Kingdom. Frequent co-authors include Libor Přeučil, Tomáš Krajník, Petr Váňa, Martin Saska, Petr Čížek, Miroslav Kulich, Vojtěch Vonásek, Robert Pěnička, Daniel Fišer and Geoffrey A. Hollinger. Their work appears in journals such as IEEE Robotics and Automation Letters, Autonomous Robots, Neurocomputing, Journal of Intelligent & Robotic Systems and Robotics and Autonomous Systems.

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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