Artur Koch

About

Artur Koch is a robotics and autonomous systems researcher whose work sits at the intersection of indoor localization, RFID-based navigation, and computer vision for mobile robots. With a body of work accumulating over 130 citations, Koch has made meaningful contributions to two complementary research threads that together advance the capabilities of intelligent indoor robots. His most influential contributions center on passive UHF RFID technology for robot localization and navigation. Through a series of papers spanning 2011 to 2016, Koch developed and refined location fingerprinting techniques using received signal strength, probabilistic similarity models, and 3D sensor modeling — work that has collectively earned over 60 citations. Notably, he demonstrated practical path-following systems that allow robots to navigate unknown environments guided purely by RFID signals, bridging theoretical localization methods with real-world deployment. Equally significant is Koch's parallel work on RGB-D perception for indoor robots. His fruit classification system (22 citations) and salient region detection research showcase his ability to build robust visual recognition pipelines that handle challenging real-world conditions such as varying lighting and pose. Together, these research threads position Koch as a versatile contributor to the field of autonomous indoor robotics, offering robots both the spatial awareness and visual intelligence needed for practical operation.

Research Focus

Key Achievements

Top Papers

1. 1
   Efficient self-adjusting, similarity-based location fingerprinting with passive UHF RFID

   23 citations · 2011
2. 2
   Multi-class fruit classification using RGB-D data for indoor robots

   22 citations · 2013
3. 3
   RFID-enabled location fingerprinting based on similarity models from probabilistic similarity measures

   19 citations · 2016
4. 4
   Salient regions detection for indoor robots using RGB-D data

   15 citations · 2015
5. 5
   Path following with passive UHF RFID received signal strength in unknown environments

   13 citations · 2012
6. 6
   Object Recognition and Tracking for Indoor Robots Using an RGB-D Sensor

   12 citations · 2015
7. 7
   Mapping UHF RFID tags with a mobile robot using a 3D sensor model

   9 citations · 2013
8. 8
   Path following for indoor robots with RFID received signal strength

   7 citations · 2011
9. 9
   Superpixel segmentation based gradient maps on RGB-D dataset

   5 citations · 2015
10. 10
    Mapping of passive UHF RFID tags with a mobile robot using outlier detection and negative information

    4 citations · 2014

Key Collaborators

Contact & Links