Krzysztof Rokosz
Papers
1
Total Citations
2
H-Index
1
About
Krzysztof Rokosz is a researcher at the forefront of safe human-robot collaboration, with a primary focus on leveraging deep learning to enhance workplace safety. His work centers on evaluating the accuracy and efficiency of object detection models in shared human-robot environments, addressing critical challenges in data acquisition and AI architecture selection. His most-cited paper, "Efficiency analysis of deep learning-based object detection for safe human robot collaboration" (2024), has already garnered 2 citations, reflecting the timely relevance of his contributions to industrial safety and automation. Rokosz’s research bridges the gap between artificial intelligence and practical robotics, aiming to predict and prevent collisions in dynamic workspaces. By systematically analyzing how different deep learning models perform under real-world conditions, he provides essential guidelines for deploying robust detection systems. His work is particularly valuable for students and engineers seeking to implement reliable safety protocols in collaborative robotics, offering both theoretical insights and actionable performance benchmarks. Rokosz’s contributions are poised to influence the next generation of intelligent manufacturing and human-robot interaction systems.
Research Focus
Key Achievements
Top Papers
- 1