Michael Everett

1.8k total citations · 1 hit paper
25 papers, 968 citations indexed

About

Michael Everett is a scholar working on Artificial Intelligence, Automotive Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michael Everett has authored 25 papers receiving a total of 968 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 9 papers in Automotive Engineering and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michael Everett's work include Robotic Path Planning Algorithms (9 papers), Autonomous Vehicle Technology and Safety (8 papers) and Reinforcement Learning in Robotics (6 papers). Michael Everett is often cited by papers focused on Robotic Path Planning Algorithms (9 papers), Autonomous Vehicle Technology and Safety (8 papers) and Reinforcement Learning in Robotics (6 papers). Michael Everett collaborates with scholars based in United States, United Kingdom and Netherlands. Michael Everett's co-authors include Jonathan P. How, Yu Fan Chen, Miao Liu, Brett T. Lopez, Jesus Tordesillas, Javier Alonso–Mora, Bruno Brito, Jonathan Fink, Philip R. Osteen and Plamen Angelov and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Robotics.

In The Last Decade

Michael Everett

24 papers receiving 929 citations

Hit Papers

Socially aware motion planning with deep reinforcement le... 2017 2026 2020 2023 2017 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Socially aware motion planning with deep reinforcement learning
    2017 463 citations Yu Fan Chen, Michael Everett et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Everett United States 12 566 374 268 218 200 25 968
Yu Fan Chen United States 9 439 0.8× 288 0.8× 220 0.8× 115 0.5× 138 0.7× 13 700
Miao Liu China 10 343 0.6× 307 0.8× 173 0.6× 111 0.5× 186 0.9× 33 707
Christoph Sprunk Germany 13 776 1.4× 239 0.6× 218 0.8× 412 1.9× 326 1.6× 18 1.1k
Anne Spalanzani France 16 680 1.2× 239 0.6× 259 1.0× 230 1.1× 261 1.3× 51 1.1k
Brandon Luders United States 14 530 0.9× 180 0.5× 250 0.9× 319 1.5× 213 1.1× 18 804
Lei Tai Hong Kong 12 1.0k 1.8× 582 1.6× 213 0.8× 488 2.2× 239 1.2× 20 1.4k
Pinxin Long China 12 637 1.1× 365 1.0× 206 0.8× 272 1.2× 234 1.2× 13 1.1k
Jacob Lambert Japan 6 506 0.9× 216 0.6× 530 2.0× 246 1.1× 184 0.9× 8 1.2k
Tingxiang Fan Hong Kong 12 337 0.6× 188 0.5× 113 0.4× 194 0.9× 124 0.6× 16 576
Soeren Kammel Germany 8 505 0.9× 174 0.5× 426 1.6× 226 1.0× 209 1.0× 13 1.1k

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-authorship network of co-authors of Michael Everett

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Everett. A scholar is included among the top collaborators of Michael Everett 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 Michael Everett. Michael Everett 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
1.
Everett, Michael, et al.. (2025). Chance-Constrained Convex MPC for Robust Quadruped Locomotion Under Parametric and Additive Uncertainties. IEEE Robotics and Automation Letters. 10(8). 8388–8395. 1 indexed citations
2.
Omidshafiei, Shayegan, et al.. (2024). Collision Avoidance Verification of Multiagent Systems With Learned Policies. IEEE Control Systems Letters. 8. 652–657.
3.
Osteen, Philip R., Stephen Phillips, Jiuguang Wang, et al.. (2024). EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy. IEEE Transactions on Robotics. 40. 3756–3777. 21 indexed citations
4.
Everett, Michael, et al.. (2023). A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops. 3523–3528. 2 indexed citations
5.
Everett, Michael, et al.. (2023). Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments. 11297–11304. 26 indexed citations
6.
Everett, Michael, et al.. (2022). Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2931–2937. 35 indexed citations
7.
Everett, Michael, et al.. (2022). Backward Reachability Analysis for Neural Feedback Loops. 2022 IEEE 61st Conference on Decision and Control (CDC). 2897–2904. 9 indexed citations
8.
Tagliabue, Andrea, Dong Ki Kim, Michael Everett, & Jonathan P. How. (2022). Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC. 2022 International Conference on Robotics and Automation (ICRA). 462–468. 14 indexed citations
9.
Tordesillas, Jesus, Brett T. Lopez, Michael Everett, & Jonathan P. How. (2021). FASTER: Fast and Safe Trajectory Planner for Navigation in Unknown Environments. IEEE Transactions on Robotics. 38(2). 922–938. 104 indexed citations
10.
Brito, Bruno, Michael Everett, Jonathan P. How, & Javier Alonso–Mora. (2021). Where to go Next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments. IEEE Robotics and Automation Letters. 6(3). 4616–4623. 48 indexed citations
11.
Everett, Michael, Yu Fan Chen, & Jonathan P. How. (2021). Collision Avoidance in Pedestrian-Rich Environments With Deep Reinforcement Learning. IEEE Access. 9. 10357–10377. 130 indexed citations
12.
Everett, Michael, et al.. (2020). Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning. arXiv (Cornell University). 23 indexed citations
13.
Chen, Yu Fan, Michael Everett, Miao Liu, & Jonathan P. How. (2017). Socially aware motion planning with deep reinforcement learning. 1343–1350. 463 indexed citations breakdown →
14.
Omidshafiei, Shayegan, Shih‐Yuan Liu, Michael Everett, et al.. (2017). Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. DSpace@MIT (Massachusetts Institute of Technology). 42. 871–878. 3 indexed citations
15.
Feigin, Micha, et al.. (2014). Seeing around corners with a mobile phone?. 1–1. 2 indexed citations
16.
Barik, Titus, Michael Everett, Rogelio E. Cardona-Rivera, David L. Roberts, & Edward F. Gehringer. (2013). A community college blended learning classroom experience through Artificial Intelligence in Games. 1525–1531. 17 indexed citations
17.
Angelov, Plamen, et al.. (2008). A Passive Approach to Autonomous Collision Detection and Avoidance in Uninhabited Aerial Systems.. Lancaster EPrints (Lancaster University). 12 indexed citations
18.
Angelov, Plamen, et al.. (2008). A Passive Approach to Autonomous Collision Detection and Avoidance. 14. 64–69. 20 indexed citations
19.
Angelov, Plamen, et al.. (2007). UAV collision avoidance - state of the art and possible solutions.. Lancaster EPrints (Lancaster University). 2 indexed citations
20.
Patel, Rupal, Michael Everett, & Eldar Sadikov. (2006). Loudmouth:. 27. 227–228. 11 indexed citations

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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