Antonio Loquercio

3.1k citations
27 papers · 1.4k · 1 hit paper · h-index 13

Impact in

Papers in

Antonio Loquercio

24 papers receiving 1.3k citations

Hit Papers

Champion-level drone racing using deep reinforcement learning 2023 · 286 citations
2860+1+2Years since publication50100150200250

Peers

Antonio Loquercio
Comparison fields: 5 of 99
  • Computer Vision and Pattern Recognition 711
  • Aerospace Engineering 522
  • Automotive Engineering 152
  • Artificial Intelligence 381
  • Control and Systems Engineering 229
Replace Hanna Kurniawati with:
Hanna Kurniawati Australia
Byron Boots United States
Hongkai Yu United States
Robert Laganière Canada
Igor Gilitschenski United States
Erion Plaku United States
Liang Zhang China
Dirk Langer United States
Jennifer Dolson United States
Seiichi Mita Japan
Antonio Loquercio relative to Hanna Kurniawati Australia Hanna Kurniawati's profile →
Citations per field
00.5×6.3×
Hanna Kurniawati · 1×
Citations per year

Countries citing papers authored by Antonio Loquercio

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Loquercio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Antonio Loquercio, 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 Antonio Loquercio Line = papers co-authored together Antonio Loquercio links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018317
2
Champion-level drone racing using deep reinforcement learning
Hit paper breakdown →
2023286
3 2020182
4 2019161
5 2019120
6 201974
7 202271
8 202437
9 202323
10 202122
11 202221
12 202315
13 202412
14 201711
15 20209
16 20176
17 20205
18 20234
19 20174
20 20243

About Antonio Loquercio

Antonio Loquercio is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Control and Systems Engineering and Automotive Engineering, having authored 27 papers that have together received 1.4k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (11 papers), Robotic Path Planning Algorithms (11 papers), Reinforcement Learning in Robotics (6 papers), Advanced Vision and Imaging (6 papers), Autonomous Vehicle Technology and Safety (4 papers), Advanced Neural Network Applications (3 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Robot Manipulation and Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (711 citations), Aerospace Engineering (522 citations), Automotive Engineering (152 citations), Artificial Intelligence (381 citations) and Control and Systems Engineering (229 citations). Antonio Loquercio has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Davide Scaramuzza, Elia Kaufmann, Ana I. Maqueda, Carlos R. del‐Blanco, Vladlen Koltun, Mattia Segù, Leonard Bauersfeld, Matthias Müller, René Ranftl and Alexey Dosovitskiy. Their work appears in journals such as IEEE Transactions on Robotics, IEEE Internet of Things Journal, IEEE Robotics and Automation Letters, IEEE Robotics & Automation Magazine and Nature.

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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