Prof. Achim Lilienthal | LiDAR Perception | Research Excellence Award

Prof. Achim Lilienthal | LiDAR Perception | Technical University of Munich | Germany

Prof. Dr. Achim Josef Lilienthal earned his Ph.D. in Computer Science at the University of Tübingen (summa cum laude), following a diploma in Physics from the University of Konstanz. Over his distinguished career, Achim Josef Lilienthal has held leading academic and research-oriented roles across Europe and beyond, including his current appointment as Full Professor (W3), Chair of Perception for Intelligent Systems at the Technical University of Munich (TUM), and Deputy Director at the Munich Institute of Robotics and Machine Intelligence (MIRMI). He previously served as full professor at Örebro University, founding and directing the Mobile Robotics & Olfaction Lab, and has been a visiting professor at institutions such as Cornell University, as well as a consultant for industry including Bosch and robotics startups. His research interests span mobile robot olfaction (gas distribution mapping and gas source localization), 3D perception and SLAM (LiDAR/radar mapping, sensor fusion, localization), human–robot interaction (intention recognition, human-aware navigation), and eye-tracking–based AI systems for human–robot interaction, driver monitoring, and safety applications. He is skilled in robotics, sensor fusion, 3D mapping, machine learning, perception algorithms, gas-sensing robotics, human-robot interface design, and systems integration enabling development of autonomous intelligent systems capable of robust perception in complex, dynamic environments. Through a prolific publication record of over 300 peer-reviewed papers, supervision of 50+ PhD students, leadership of major EU research projects and startups, and securing substantial research funding, Achim Josef Lilienthal has made foundational contributions to the robotics and intelligent systems community particularly gas-sensing robotics, safe human-machine interaction, and autonomous perception.

Professional Profiles: ORCID | Google Scholar | Scopus

Selected publications

Lilienthal, A. J., & Duckett, T. (2007). Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics, 24(10), 803–827. (Citations: 951)
Triebel, R., Arras, K., Alami, R., Beyer, L., Breuers, S., Chatila, R., Chetouani, M., … & Lilienthal, A. J. (2016). Spencer: A socially aware service robot for passenger guidance and help in busy airports. Field and Service Robotics: Results of the 10th International Conference. (Citations: 364)
Magnusson, M., Nüchter, A., Lorken, C., & Lilienthal, A. J. (2009). Evaluation of 3D registration reliability and speed – A comparison of ICP and NDT. IEEE International Conference on Robotics and Automation (ICRA). (Citations: 348)
Valgren, C., & Lilienthal, A. J. (2010). SIFT, SURF & Seasons: Appearance-based Long-term Localization in Outdoor Environments. Robotics and Autonomous Systems, 58(2), 149–156. (Citations: 314)
Stoyanov, T., Magnusson, M., Andreasson, H., & Lilienthal, A. J. (2012). Fast and Accurate Scan Registration through Minimization of the Distance between Compact 3D NDT Representations. International Journal of Robotics Research, 31(12), 1377–1393. (Citations: 303)
Neumann, P. P., Hernández Bennetts, V., & Lilienthal, A. J. (2013). Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms. Advanced Robotics, 27(9), 725–738. (Citations: 270)
Lilienthal, A. J., & Duckett, T. (2004). Building gas concentration gridmaps with a mobile robot. Robotics and Autonomous Systems, 48(1), 3–16. (Citations: 210)

Mr. Zhibo Cui, Tarim University, China

Zhibo Cui is a dedicated researcher specializing in sensor technology and remote sensing applications. He obtained his Bachelor’s degree in Agricultural Resources and Environment from the College of Agriculture at Tarim University in 2023 and is currently pursuing a Master’s degree in Resource Utilization and Plant Protection at the same institution. His research focuses on the advanced utilization of Sentinel-1/2 radar and optical sensors for environmental monitoring, particularly in soil organic carbon mapping. He has made significant contributions to multi-source remote sensing data fusion and has successfully enhanced mapping accuracy using super-ensemble models. His work, published in Remote Sensing, demonstrates his expertise in sensor data processing and analysis. With a strong foundation in innovation and teamwork, Zhibo Cui continues to push the boundaries of remote sensing technology for agricultural and environmental advancements.

Professional Profile:

Suitability for Best Researcher Award

Based on the provided information, Zhibo Cui demonstrates a strong research background in sensor technology and remote sensing applications, particularly in the monitoring of soil organic carbon using Sentinel-1/2 radar and optical sensors. His work focuses on sensor data processing, multi-source remote sensing data fusion, and high-accuracy mapping, which are relevant and impactful areas of study.

🏆 Achievements:

📡 Advanced Research in Remote Sensing – Unveiled complex correlations between Sentinel-1/2 data and soil organic carbon

🌍 High-Precision Soil Organic Carbon Mapping – Led a project integrating environmental covariates with a super-ensemble model

✍ Published Research – “High-Accuracy Mapping of Soil Organic Carbon by Mining Sentinel-1/2 Radar and Optical Time-Series Data with Super Ensemble Model” in Remote Sensing journal