Papers
15
Total Citations
494
H-Index
10
About
Simon Kriegel is a robotics researcher whose work sits at the intersection of autonomous 3D modeling, robotic perception, and mobile manipulation. He is perhaps best known for pioneering next-best-scan (NBS) and next-best-view (NBV) planning strategies, which enable robots to autonomously and efficiently construct complete 3D surface models of unknown objects by intelligently selecting optimal scanning positions. His landmark 2013 paper on efficient next-best-scan planning has garnered 164 citations, establishing him as a leading voice in autonomous object reconstruction. Building on this foundation, Kriegel extended his research into active scene exploration, combining object recognition and autonomous modeling to enable robots to analyze and map complex, partially known environments. His contributions to industrial robotics are equally significant — his work on fully autonomous mobile manipulation and pick-and-place operations demonstrates a practical vision for deploying unskilled-configurable robotic systems in real industrial settings. More recently, Kriegel has expanded into space robotics, investigating pose estimation for satellites and the utility of plenoptic cameras during on-orbit servicing missions. Across more than a decade of research, his cumulative citation record reflects sustained influence on how robots perceive, model, and interact with their physical surroundings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Toward fully autonomous mobile manipulation for industrial environments73 citations · 2017
- 3Next-best-scan planning for autonomous 3D modeling55 citations · 2012
- 4
- 5Combining object modeling and recognition for active scene exploration47 citations · 2013
- 6
- 7Autonomous pick and place operations in industrial production19 citations · 2015
- 8
- 9Multi-view orientation estimation using Bingham mixture models11 citations · 2016
- 10Appearance learning for 3D pose detection of a satellite at close-range10 citations · 2017