Bartosz Ptak
Papers
2
Total Citations
40
H-Index
2
About
Bartosz Ptak is a researcher at the forefront of autonomous robotics and deep learning, with a focus on enabling robust, real-world perception for aerial and planetary systems. His work addresses critical challenges in autonomous landing and extraterrestrial exploration, where precision and reliability are paramount. Ptak’s most influential contribution is the development of a fast, lightweight deep learning vision pipeline for autonomous UAV landing support, a paper that has garnered 27 citations since 2024. This work tackles the complex variables of terrain, weather, and obstacles, offering a computationally efficient solution that enhances landing safety without sacrificing performance. Complementing this, Ptak introduced LunarSim, a high-fidelity lunar rover simulator integrated with ROS 2, designed for advanced computer vision algorithm development. With 13 citations since 2023, LunarSim provides a vital tool for training and evaluating algorithms in realistic lunar conditions, bridging the gap between simulation and deployment. Through these contributions, Ptak demonstrates a commitment to practical, scalable solutions that push the boundaries of autonomous navigation, making his research essential reading for those working in field robotics and space exploration.
Research Focus
Key Achievements
Top Papers
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- 2