Papers
44
Total Citations
903
H-Index
16
About
Max Pfingsthorn is a leading roboticist whose research spans autonomous navigation, multi-robot systems, and human-robot interaction, with a particular focus on safety and accessibility. His most impactful contributions lie in 3D mapping and SLAM (Simultaneous Localization and Mapping), where he pioneered a fast, closed-form pose-graph relaxation technique that registers large planar surface segments from range sensor point-clouds. This work, detailed in his highly cited 2009 paper (108 citations), enables efficient and consistent 3D map construction for mobile robots in planar environments. Pfingsthorn also advanced multi-robot SLAM with a scalable hybrid method (72 citations), allowing for highly detailed maps through collaborative exploration. His research extends to critical applications: he co-developed a UAV system for safety, security, and rescue missions (130 citations), and explored robotic systems for nursing care (48 citations) and collaborative robots for people with disabilities in sheltered workshops (31 citations). Additionally, his work on Augmented Reality visualizations for industrial robot safety (34 citations) and dexterous underwater inspection (33 citations) demonstrates his versatility. With over 500 total citations, Pfingsthorn’s work has profoundly influenced autonomous mapping, rescue robotics, and inclusive robotic design.
Research Focus
Key Achievements
Top Papers
- 1Safety, Security, and Rescue Missions with an Unmanned Aerial Vehicle (UAV)130 citations · 2011
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- 3A Scalable Hybrid Multi-robot SLAM Method for Highly Detailed Maps72 citations · 2008
- 4Fast 3D mapping by matching planes extracted from range sensor point-clouds55 citations · 2009
- 5A Survey of Robotic Systems for Nursing Care48 citations · 2022
- 6Mind the ARm34 citations · 2020
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- 10Determining Map Quality through an Image Similarity Metric29 citations · 2009