Michael Everett

1.9k citations
26 papers · 1.0k · 1 hit paper · h-index 12

Impact in

Papers in

Michael Everett

25 papers receiving 1000 citations

Michael Everett's Hit Papers

Socially aware motion planning with deep reinforcement learning 2017 · 497 citations
4970+3+6Years since publication100200300400

Peers

Michael Everett
Comparison fields: 5 of 67
  • Computer Vision and Pattern Recognition 594
  • Automotive Engineering 283
  • Ocean Engineering 207
  • Artificial Intelligence 399
  • Aerospace Engineering 225
Replace Yu Fan Chen with:
Yu Fan Chen United States
Miao Liu China
Christoph Sprunk Germany
Pinxin Long China
Gonzalo Ferrer Russia
Anne Spalanzani France
Jeremy Ma United States
Xuesu Xiao United States
Hao Xiang United States
Tirthankar Bandyopadhyay Australia
Michael Everett relative to Yu Fan Chen United States Yu Fan Chen's profile →
Citations per field
00.5×3.3×
Yu Fan Chen · 1×
Citations per year

Countries citing papers authored by Michael Everett

Since Specialization
Citations

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

Fields of papers citing papers by Michael Everett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Everett, 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 Michael Everett Line = papers co-authored together Michael Everett 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
Socially aware motion planning with deep reinforcement learning
Hit paper breakdown →
2017497
2 2021139
3 2021109
4 202152
5 202238
6 202329
7 202424
8 202023
9 200822
10 201317
11 202215
12
A Passive Approach to Autonomous Collision Detection and Avoidance in Uninhabited Aerial Systems.
200812
13 200611
14 202210
15 20238
16 20238
17 20065
18 20234
19 20173
20 20233

About Michael Everett

Michael Everett is a scholar working on Artificial Intelligence, Automotive Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering, having authored 26 papers that have together received 1.0k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (9 papers), Autonomous Vehicle Technology and Safety (8 papers), Reinforcement Learning in Robotics (6 papers), Robotics and Sensor-Based Localization (5 papers), Adversarial Robustness in Machine Learning (5 papers), Cardiac Arrest and Resuscitation (3 papers), Fault Detection and Control Systems (3 papers) and Air Traffic Management and Optimization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (594 citations), Automotive Engineering (283 citations), Ocean Engineering (207 citations), Artificial Intelligence (399 citations) and Aerospace Engineering (225 citations). Michael Everett has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Jonathan P. How, Yu Fan Chen, Miao Liu, Brett T. Lopez, Jesus Tordesillas, Bruno Brito, Javier Alonso–Mora, Jonathan Fink, Philip R. Osteen and Plamen Angelov. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Control Systems Letters, IEEE Transactions on Robotics, IEEE Access and 2022 IEEE 61st Conference on Decision and Control (CDC).

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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