Joris IJsselmuiden
Papers
7
Total Citations
530
H-Index
6
About
Joris IJsselmuiden is a leading researcher at the intersection of agricultural robotics and computer vision, whose work is transforming how autonomous systems perceive and operate in complex, unstructured environments. His primary research areas include semantic segmentation, multi-robot systems, and sensor-based perception for agriculture and animal husbandry. IJsselmuiden’s most impactful contribution is his pioneering work on data synthesis methods for semantic segmentation in agriculture, exemplified by his highly cited 2017 paper on the *Capsicum annuum* dataset (186 citations), which addresses the critical bottleneck of large-scale annotation for deep learning models. He has also made significant advances in robot navigation for orchards, developing robust localization techniques using Particle and Kalman filters (150 citations), and has explored the use of robot swarms for monitoring and mapping in agricultural settings (128 citations). Notably, he led the development of PoultryBot, an autonomous mobile robot for poultry houses, demonstrating practical applications of his object discrimination and segmentation methods. With a total of over 530 citations across his key works, IJsselmuiden’s research is essential reading for anyone interested in bridging the gap between state-of-the-art computer vision and the real-world demands of agricultural robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Monitoring and mapping with robot swarms for agricultural applications128 citations · 2017
- 4
- 5Object discrimination in poultry housing using spectral reflectivity12 citations · 2018
- 6
- 7Object segmentation in poultry housings using spectral reflectivity3 citations · 2015