Patrick Fleischmann was born in Mainz in 1984 and completed his Abitur (university-entrance diploma) in 2003 at the Gymnasium in Nieder-Olm (Rhineland-Palatinate). He attended the University of Kaiserslautern from 2003 until he graduated with a degree in Diplom-Technoinformatik (a bridged course of approximately equal proportions of computer science and electrical engineering) in 2010. Parallel to his studies he worked as a research assistant at the Fraunhofer Institute for Industrial Mathematics ITWM and at the Institute for Mobility and Transport (imove). He completed his diploma thesis at the Robotics Research Lab. His work was the integration of aerial images into the navigation system of the autonomous outdoor robot RAVON.
From September 2010 Patrick Fleischmann worked as a doctoral fellow at the Robotics Research Lab, since the end of 2012 he is employed as a research assistant. His research interests lie in the area of robust sensor data processing for environmental modeling and recognition. He gained practical experience in projects with industrial partners like John Deere GmbH & Co. KG, where he has developed prototypical assistance systems for future tractors.
- Detection of Field Structures for Agricultural Vehicle Guidance.
KI - Künstliche Intelligenz, S. 1 - 7. (2013)
- Trajectory Planning and Lateral Control for Agricultural Guidance Applications.
The 2013 ICITA Journal of Information Technology and Applications, (2013)
- Principles in Framework Design applied in Networked Robotics.
Proceedings of the 3rd IFAC Symposium on Telematics Applications, S. 150 - 155. (2013)
- A Stereo Vision Based Obstacle Detection System for Agricultural Applications.
Proceedings of Field and Service Robotics (FSR), (2015)
- Using OpenStreetMap for Autonomous Mobile Robot Navigation.
Proceedings of the 14th International Conference on Intelligent Autonomous Systems (IAS-14), (2016)
- Field and Service Robotics. Results of the 10th International Conference.
- An Adaptive Detection Approach for Autonomous Forest Path Following using Stereo Vision.
Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision (ICARCV 2016), (2016)
- Segmentation of Very Sparse and Noisy Point Clouds.
ICACR 2019, S. 119124. (2019)
- Crop Edge Detection based on Stereo Vision.
Intelligent Autonomous Systems 15 – Proceedings of the 15th International Conference IAS-15, Vol. 867, (2019)
- Commercial Vehicle Technology 2018 – Proceedings of the 5th Commercial Vehicle Technology Symposium - CVT 2018.