Pavel Karpyshev
Papers
8
Total Citations
169
H-Index
7
About
Pavel Karpyshev is a robotics researcher whose work spans autonomous navigation, perception, and multi-robot systems for challenging environments. His key research areas include agricultural robotics, planetary exploration, and warehouse automation, with a focus on integrating computer vision and neural fields into practical robotic platforms. Among his most impactful contributions is a 2021 study on an autonomous mobile robot for apple plant disease detection, which combines CNN-based analysis with multi-spectral vision and has garnered 46 citations. This work demonstrates his ability to address real-world agricultural challenges through sensor fusion and machine learning. Karpyshev also introduced MeSLAM, a memory-efficient SLAM system based on neural fields (23 citations), which tackles scalability issues in long-term robot operation. His NFOMP framework (23 citations) advances optimal motion planning for nonholonomic robots, while his two-wheeled robotic swarm concept for Mars exploration (28 citations) showcases innovative thinking for extraterrestrial missions. Additional notable work includes impedance-based control for soft UAV landing on ground robots and customer behavior analytics using RFID-equipped autonomous systems. With over 150 total citations and a growing portfolio of high-impact publications, Karpyshev is establishing himself as a versatile roboticist whose work bridges theoretical advances and deployment-ready solutions across agriculture, space, and service robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2The two-wheeled robotic swarm concept for Mars exploration28 citations · 2022
- 3
- 4MeSLAM: Memory Efficient SLAM based on Neural Fields23 citations · 2022
- 5
- 6Customer behavior analytics using an autonomous robotics-based system16 citations · 2020
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