Papers
20
Total Citations
263
H-Index
8
About
Janko Petereit is a robotics researcher whose work centers on autonomous mobile systems, with particular expertise in path planning, multi-sensor localization, and robot perception in unstructured outdoor environments. His most cited contribution — "Application of Hybrid A* to an Autonomous Mobile Robot for Path Planning in Unstructured Outdoor Environments" (2022, 64 citations) — addresses the formidable challenge of navigating nonholonomic robots across complex terrain blending structured roads and open wilderness, offering a practically impactful solution to a long-standing problem in field robotics. His involvement in the ROBDEKON project (2019, 45 citations) demonstrates a strong commitment to socially consequential applications, developing robotic systems capable of decontaminating radioactive and chemically hazardous sites and reducing human exposure to danger. More recently, Petereit contributed the GOOSE dataset (2024, 27 citations), advancing deep learning-based perception for autonomous systems operating in data-scarce outdoor settings. Spanning over a decade of research, his algorithm toolboxes, multi-sensor fusion frameworks, and disaster management robotics reflect a sustained effort to make autonomous robots safer, smarter, and deployment-ready in real-world, high-stakes scenarios — an increasingly vital frontier as autonomous systems expand beyond controlled environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2ROBDEKON: Robotic Systems for Decontamination in Hazardous Environments45 citations · 2019
- 3The GOOSE Dataset for Perception in Unstructured Environments27 citations · 2024
- 4
- 5Algorithm Toolbox for Autonomous Mobile Robotic Systems16 citations · 2017
- 6Situation responsive networking of mobile robots for disaster management15 citations · 2022
- 7
- 8
- 9
- 10Machine learning for the perception of autonomous construction machinery7 citations · 2023