Brian Plancher

24 papers receiving 358 citations

Peers

Brian Plancher
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 123
  • Computer Science Applications 32
  • Control and Systems Engineering 114
  • Hardware and Architecture 32
  • Automotive Engineering 47
Replace Fernando Díaz-del-Río with:
Fernando Díaz-del-Río Spain
Suzana Uran Slovenia
Nalini C. Iyer India
Ruffin White United States
Stefan Enderle Germany
Dongguo Zhou China
Roland Hafner Germany
Chan‐Jin Chung United States
Wenju Zhou China
Paul Lister United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Brian Plancher

Since Specialization
Citations

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

Fields of papers citing papers by Brian Plancher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201771
2 201733
3 202130
4 202129
5 202227
6 202021
7 202419
8 202219
9 202317
10 202216
11 202316
12 202311
13 202411
14 202211
15 20219
16 20248
17 20234
18 20193
19 20223
20 20242

About Brian Plancher

Brian Plancher is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering, having authored 26 papers that have together received 365 indexed citations. Recurring topics across this work include Robotic Locomotion and Control (6 papers), Robotic Path Planning Algorithms (5 papers), Robotics and Sensor-Based Localization (4 papers), Modular Robots and Swarm Intelligence (4 papers), Reinforcement Learning in Robotics (4 papers), Embedded Systems Design Techniques (2 papers), Software Engineering Research (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (123 citations), Computer Science Applications (32 citations), Control and Systems Engineering (114 citations), Hardware and Architecture (32 citations) and Automotive Engineering (47 citations). Brian Plancher has collaborated with scholars based in United States, Australia and Ireland. Frequent co-authors include Vijay Janapa Reddi, Scott Kuindersma, Zachary Manchester, Thomas Bourgeat, Srinivas Devadas, R.T. Shin, Sertaç Karaman, Pete Warden, Matthew Stewart and Colby Banbury. Their work appears in journals such as Communications of the ACM, ACM Transactions on Computer Systems, IEEE Robotics & Automation Magazine, IEEE Robotics and Automation Letters and Nature Machine Intelligence.

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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