Steve Macenski
Impact in
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- Robotic Path Planning Algorithms
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- Robotics and Automated Systems
- Robot Manipulation and Learning
Papers in
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- Robotics and Sensor-Based Localization 5
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- Robotic Path Planning Algorithms 4
- Advanced Vision and Imaging 1
- Co-authors
- Brian Gerkey (1 shared paper)Tully Foote (1 shared paper)Jonatan Ginés (2 shared papers)Francisco Martín (2 shared papers)Ruffin White (1 shared paper)David Tsai (1 shared paper)Max Feinberg (1 shared paper)Tom Moore (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (1 paper)Science Robotics (1 paper)Autonomous Robots (1 paper)Robotics and Autonomous Systems (1 paper)International Journal of Advanced Robotic Systems (1 paper)
- Partner nations
- United StatesSpainRussia
In The Last Decade
Steve Macenski
10 papers receiving 1.1k citations
Steve Macenski's Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 468
- Control and Systems Engineering 350
- Aerospace Engineering 360
- Industrial and Manufacturing Engineering 102
- Hardware and Architecture 55
Countries citing papers authored by Steve Macenski
This map shows the geographic impact of Steve Macenski'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 Steve Macenski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Macenski more than expected).
Fields of papers citing papers by Steve Macenski
This network shows the impact of papers produced by Steve Macenski. 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 Steve Macenski. The network helps show where Steve Macenski may publish in the future.
Co-authors
The 10 scholars most cited alongside Steve Macenski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Robot Operating System 2: Design, architecture, and uses in the wild Hit paper breakdown → | 2022 | 687 |
| 2 | 2020 | 190 | |
| 3 | 2021 | 72 | |
| 4 | 2023 | 51 | |
| 5 | 2021 | 48 | |
| 6 | 2023 | 43 | |
| 7 | 2020 | 37 | |
| 8 | 2023 | 31 | |
| 9 | 2019 | 2 | |
| 10 | 2018 | 1 | |
| 11 | 2026 | 0 |
About Steve Macenski
Steve Macenski is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering, Mechanical Engineering and Computer Networks and Communications, having authored 11 papers that have together received 1.2k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (5 papers), Robotic Path Planning Algorithms (4 papers), Modular Robots and Swarm Intelligence (3 papers), Robotics and Automated Systems (3 papers), Distributed systems and fault tolerance (2 papers), Advanced Vision and Imaging (1 paper), Underwater Vehicles and Communication Systems (1 paper) and Reinforcement Learning in Robotics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (468 citations), Control and Systems Engineering (350 citations), Aerospace Engineering (360 citations), Industrial and Manufacturing Engineering (102 citations) and Hardware and Architecture (55 citations). Steve Macenski has collaborated with scholars based in United States, Spain and Russia. Frequent co-authors include Brian Gerkey, Tully Foote, Jonatan Ginés, Francisco Martín, Ruffin White, David Tsai, Max Feinberg, Tom Moore, Michael A. J. Ferguson and David V. Lu. Their work appears in journals such as IEEE Robotics and Automation Letters, Science Robotics, Autonomous Robots, Robotics and Autonomous Systems and International Journal of Advanced Robotic Systems.
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.