Agricultural Robotics

Our work is centered on robotic/computer vision to enable robots and autonomous systems to work in challenging environments (especially agriculture). Important areas of research are agricultural robots and autonomous systems as well as scalable classification and learning approaches. You can find out more about our research here.


Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar” will be presented at DICTA 2020! Congratulations to all the authors: Michael Halstead, Simon Denman, Clinton Fookes and Chris McCool.

LiDAR Panoptic Segmentation for Autonomous Driving” was presented at IROS 2020! Congratulations to all the authors: Andres Milioto, Jens Behley, Chris McCool, and Cyrill Stachniss.

Article on sweet pepper arvesting has been published in the Journal of Field Robotics “Performance Improvements of a Sweet Pepper Harvesting Robot in Protected Cropping Environments”, C. Lehnert, C. McCool, I. Sa and T. Perez.

Panoptic Segmentation of LiDAR was recently accepted to IROS “LiDAR Panoptic Segmentation for Autonomous Driving, A. Milioto, J. Behley, C. McCool and C. Stachniss.

In January this year (2020) we were joined by two new PhD candidates Claus Smitt and Alireza Ahmadi.