Graeme Best

32 papers receiving 549 citations

Peers

Graeme Best
Comparison fields: 5 of 61
  • Computer Vision and Pattern Recognition 279
  • Aerospace Engineering 186
  • Computer Networks and Communications 168
  • Artificial Intelligence 197
  • Ocean Engineering 63
Replace Pratap Tokekar with:
Pratap Tokekar United States
Chengping Zhou China
Chengzhi Qu China
Lisane Brisolara Brazil
Christian Schlegel Germany
Tingxiang Fan Hong Kong
Heng Zhang China
Xiaojia Xiang China
D. Wilkes Canada
Chao Yan China
Graeme Best relative to Pratap Tokekar United States Pratap Tokekar's profile →
Citations per field
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Citations per year

Countries citing papers authored by Graeme Best

Since Specialization
Citations

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

Fields of papers citing papers by Graeme Best

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018126
2 201546
3 201746
4 201841
5 202135
6 201926
7 201625
8 201625
9 202224
10
Terrain classification using a hexapod robot
201321
11 201721
12 202116
13 202015
14 202113
15 201812
16 202311
17 202010
18 20158
19 20237
20 20197

About Graeme Best

Graeme Best is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics, having authored 33 papers that have together received 566 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (12 papers), Robotics and Sensor-Based Localization (10 papers), Optimization and Search Problems (6 papers), Distributed Control Multi-Agent Systems (5 papers), Reinforcement Learning in Robotics (4 papers), Vehicle Routing Optimization Methods (2 papers), Artificial Intelligence in Games (2 papers) and Topological and Geometric Data Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (279 citations), Aerospace Engineering (186 citations), Computer Networks and Communications (168 citations), Artificial Intelligence (197 citations) and Ocean Engineering (63 citations). Graeme Best has collaborated with scholars based in United States, Australia and Czechia. Frequent co-authors include Robert Fitch, Geoffrey A. Hollinger, Ramgopal R. Mettu, Jan Faigl, Oliver M. Cliff, Timothy Patten, Sebastian Scherer, Robert Pěnička, John M. Keller and Peyman Moghadam. Their work appears in journals such as Autonomous Robots, IEEE Robotics and Automation Letters, The International Journal of Robotics Research, Journal of Field Robotics and IEEE Transactions on Robotics.

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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