Mateusz Kujawiński
Papers
4
Total Citations
46
H-Index
3
About
Mateusz Kujawiński is a robotics researcher whose work centers on energy-efficient autonomous systems, with a particular focus on mobile robots and unmanned aerial vehicles (UAVs). His most impactful contribution, "Machine Learning in Creating Energy Consumption Model for UAV" (2022, 30 citations), introduces a novel machine-learning approach to model and minimize energy use in UAVs—a critical challenge for extending operational range and reducing maintenance costs. Kujawiński further advances this area by comparing energy prediction algorithms for differential and skid-steer drive robots across various ground surfaces (2021, 11 citations), demonstrating that artificial neural networks can outperform traditional analytical models. Beyond energy modeling, he has practical expertise in deploying Robot Operating System (ROS) for autonomous control, as shown in his work on competitions like Eurobot and Robotour (2016), and in coordinating complex missions for the ERL Emergency Robots and University Rover Challenge (2019). His research bridges theoretical modeling and real-world robotic applications, offering valuable insights for students and engineers seeking to build more efficient, autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Machine Learning in Creating Energy Consumption Model for UAV30 citations · 2022
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