Andrea Cherubini

82 papers receiving 2.2k citations

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Collaborative manufacturing with physical human–robot int...201620262019202220162022100200300400

Peers

Andrea Cherubini
Comparison fields: 5 of 122
  • Control and Systems Engineering 910
  • Biomedical Engineering 699
  • Computer Vision and Pattern Recognition 577
  • Cognitive Neuroscience 403
  • Industrial and Manufacturing Engineering 327
Replace Tsukasa Ogasawara with:
Tsukasa Ogasawara Japan
Carlo Alberto Avizzano Italy
Carlos Balaguer Spain
Philippe Fraisse France
Jörg Krüger Germany
Jeha Ryu South Korea
Rajiv Dubey United States
Jun Ota Japan
Gentiane Venture Japan
Yasuhisa Hirata Japan
Andrea Cherubini relative to Tsukasa Ogasawara Japan Tsukasa Ogasawara's profile →
Citations per field
00.5×2.9×
Tsukasa Ogasawara · 1×
Citations per year

Countries citing papers authored by Andrea Cherubini

Since Specialization
Citations

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

Fields of papers citing papers by Andrea Cherubini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Cherubini

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Cherubini. A scholar is included among the top collaborators of Andrea Cherubini 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 Andrea Cherubini. Andrea Cherubini 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
#WorkIndexed citations
1 4
2 0
3 0
4 1
5 1
6
Challenges and Outlook in Robotic Manipulation of Deformable Objectsbreakdown →
159
7 5
8 41
9 2
10 19
11 43
12 9
13 13
14 183
15 50
16 13
17
Active calibration of tactile sensors mounted on a robotic hand
2
18
A Redundancy-Based Approach to Obstacle Avoidance Applied to Mobile Robot Navigation
3
19 215
20
A vision-based path planner/follower for an assistive robotics project
1

About Andrea Cherubini

Andrea Cherubini is a scholar working on Human-Computer Interaction, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 87 papers that have together received 2.3k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (26 papers), Robotic Path Planning Algorithms (19 papers) and Robotics and Sensor-Based Localization (18 papers). The work is most often cited by research in Human-Computer Interaction (255 citations), Control and Systems Engineering (910 citations) and Industrial and Manufacturing Engineering (327 citations). Andrea Cherubini has collaborated with scholars based in France, Italy and United States. Frequent co-authors include Philippe Fraisse, Robin Passama, André Crosnier, François Chaumette, Antoine Lasnier, Benjamin Navarro, Giuseppe Oriolo, Jihong Zhu, Giovanni Morone and Marco Iosa. Their work appears in journals such as PLoS ONE, The International Journal of Robotics Research and IEEE Transactions on Intelligent Transportation 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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