Matthias Nieuwenhuisen
University of Bonn, Fraunhofer Institute for Communication, Information Processing and Ergonomics
Papers
23
Total Citations
409
H-Index
12
About
Matthias Nieuwenhuisen is a robotics researcher whose work spans mobile manipulation, autonomous aerial vehicles, and intelligent robot perception. He has made significant contributions to the field of bin picking — the automated grasping of objects from unordered piles — demonstrating how anthropomorphic mobile robots can tackle this historically static problem in dynamic, real-world settings. His foundational papers on shape-primitive-based object recognition and active manipulation, together accumulating nearly 170 citations, established robust frameworks for robots to identify and grasp complex objects using 3D point cloud analysis. Nieuwenhuisen has also advanced the capabilities of micro aerial vehicles (MAVs), developing predictive collision avoidance systems, autonomous landing on moving targets, and multi-MAV coordination for object retrieval — work validated through competitive challenges such as MBZIRC. His chimney inspection research highlights a practical humanitarian dimension, using autonomous MAVs to replace dangerous human labor in hazardous environments. Beyond aerial systems, his contributions to mobile service robots, door-aware indoor navigation, and human-robot interaction reflect a broad commitment to deploying intelligent robots in everyday environments. With over 325 cumulative citations, Nieuwenhuisen's research meaningfully bridges perception, planning, and autonomy across both ground and aerial robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1Mobile bin picking with an anthropomorphic service robot99 citations · 2013
- 2Active Recognition and Manipulation for Mobile Robot Bin Picking40 citations · 2013
- 3Shape-Primitive Based Object Recognition and Grasping30 citations · 2012
- 4Human-Like Interaction Skills for the Mobile Communication Robot Robotinho28 citations · 2013
- 5PREDICTIVE POTENTIAL FIELD-BASED COLLISION AVOIDANCE FOR MULTICOPTERS27 citations · 2013
- 6
- 7Fast autonomous landing on a moving target at MBZIRC23 citations · 2017
- 8
- 9Learning Visual Obstacle Detection Using Color Histogram Features17 citations · 2012
- 10