Papers
174
Total Citations
6,492
H-Index
44
About
Achim J. Lilienthal is a prominent robotics researcher whose work spans mobile robot perception, autonomous navigation, and robotic olfaction — the use of robots to detect, localize, and map airborne chemical signals. Based at Örebro University, Lilienthal has made foundational contributions to 3D scan registration, a critical capability for robot mapping. His development of the Normal Distributions Transform (NDT) algorithm and its variants, including work on fast 3D NDT representations, has profoundly influenced how autonomous robots build accurate spatial maps — his 2007 paper alone has garnered over 760 citations. Equally significant is his pioneering research in gas distribution modeling, including the influential Kernel DM+V algorithm, and gas source localization using both ground robots and aerial drones. His 2013 work on bio-inspired algorithms for drone-based gas source localization (222 citations) and the remarkable Smelling Nano Aerial Vehicle demonstrate his commitment to pushing technological boundaries. Beyond sensing, Lilienthal contributed to socially aware robotics through the SPENCER airport guidance robot project. With multiple papers exceeding 150 citations, his interdisciplinary research continues to shape autonomous systems, environmental monitoring, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1Scan registration for autonomous mining vehicles using 3D‐NDT767 citations · 2007
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- 6Building gas concentration gridmaps with a mobile robot188 citations · 2004
- 7Airborne Chemical Sensing with Mobile Robots165 citations · 2006
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- 9SIFT, SURF and seasons : long-term outdoor localization using local features141 citations · 2007
- 10Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping134 citations · 2019