V. Lumelsky

6.0k total citations
106 papers, 4.1k citations indexed

About

V. Lumelsky is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering. According to data from OpenAlex, V. Lumelsky has authored 106 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Computer Vision and Pattern Recognition, 56 papers in Control and Systems Engineering and 34 papers in Aerospace Engineering. Recurrent topics in V. Lumelsky's work include Robotic Path Planning Algorithms (82 papers), Robotics and Sensor-Based Localization (34 papers) and Robot Manipulation and Learning (28 papers). V. Lumelsky is often cited by papers focused on Robotic Path Planning Algorithms (82 papers), Robotics and Sensor-Based Localization (34 papers) and Robot Manipulation and Learning (28 papers). V. Lumelsky collaborates with scholars based in United States, United Kingdom and Italy. V. Lumelsky's co-authors include Alexander A. Stepanov, M. S. Shur, S. Wagner, E. Cheung, Andrei M. Shkel, T. Skewis, Susan Hert, Kang Sun, Philipp Mittendorfer and Gordon Cheng and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Pattern Recognition.

In The Last Decade

V. Lumelsky

100 papers receiving 3.9k citations

Peers

V. Lumelsky
Comparison fields: 5 of 127
  • Computer Vision and Pattern Recognition 2.3k
  • Control and Systems Engineering 1.4k
  • Aerospace Engineering 1.4k
  • Biomedical Engineering 1.2k
  • Mechanical Engineering 755
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Citations per field, relative to V. Lumelsky
V. Lumelsky · 1×
Citations per year, relative to V. Lumelsky
V. Lumelsky · 1×

Countries citing papers authored by V. Lumelsky

Since Specialization
Citations

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

Fields of papers citing papers by V. Lumelsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Lumelsky

This figure shows the co-authorship network connecting the top 25 collaborators of V. Lumelsky. A scholar is included among the top collaborators of V. Lumelsky 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 V. Lumelsky. V. Lumelsky 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
# Work Indexed citations
1 101
2 21
3 6
4 19
5 18
6 0
7 364
8
Active Sensing In Sensor-Based Motion Planning With Dynamics
1
9 8
10 24
11
Motion planning in R 3 for multiple tethered robots.
9
12 18
13
Motion planning with uncertainty for a 3d Cartesian robot arm
5
14 67
15 32
16 3
17 1
18 53
19 7
20 6

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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