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Pankaj Deoli completed his bachelor's in Mechanical Engineering (with specialization in automotive engineering) from Graphic Era University, Dehradun, India. At the Technische Universität Kaiserslautern, he studied Commercial Vehicle Technology (with specialization in Intelligent systems) for his Master's degree. His Master Thesis at the Robotic Research Laboratory was focussed towards rock detection in earth's off-road environments, wherein the capabilities of deep neural networks for this challenging task were studied.
Since January 2022, Pankaj Deoli is a phd-student in the Robotic Research Laboratory exploring the domain of off-road environment perception for autonomous navigation. His research interests lies in imitating human minds for effective scene representation with use-cases in commercial vehicles.
Publications
2024
- Evaluating the Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks. A Dataset-Centric analysis.
arXiv, (2024) - Evaluation of Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks. A Dataset-Centric Study.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, Nr. 3, S. 22372239. (2024) - Exploring Image Fusion Techniques for Off-Road Semantic Segmentation in Harsh Lighting Conditions. A Multispectral Imagery Analysis.
Proceedings of the 21st International Conference on Ubiquotous Robots (UR2024), (2024) - Implementation of Off-Road Panoptic-Segmentation under dynamic lighting conditions.
Proceedings of 23rd International Conference on Machine Learning and Applications (ICMLA 2024) (To appear), (2024) - Understanding nature step-by-step. towards off-road environment perception for autonomous driving.
Proceedings of 6th Young Researchers Symposium (YRS 2024), (2024)
2023
- Navigating Off-roads. Using Deep neural Networks for Rock detection in off-road Autonomous Driving with Unimog.
20th International Conference on Ubiquitous Robots (UR 2023), (2023)
2022
- Traction optimization for robust navigation in unstructured environments using deep neural networks on the example of the off-road truck Unimog.
17th International Conference on Intelligent Autonomous Systems – IAS-17, S. 191 - 208. (2022) - Universelle Nutzfahrzeugkonzepte zum autonomen Arbeiten in herausfordernden Umgebungen. Ein Zwischenbericht zum Projekt »Autonome Arbeitsmaschine für den Einsatz in Anwendungen wie Katastrophenschutz/ Feuerwehr, Forstwirtschaft und Weinbau«..
CVC News, Vol. 2, S. 20 - 24. (2022)
2021