Gert Kootstra — accepted AI-conference papers

2026

AgriGS-SLAM: Orchard Mapping Across Seasons via Multi-View Gaussian Splatting SLAM

Mirko Usuelli, David Rapado Rincon, Gert Kootstra, Matteo Matteucci

RA-L 2026

Autonomous robots in orchards require real-time 3D scene understanding despite repetitive row geometry, seasonal appearance changes, and wind-driven foliage motion. We present AgriGS-SLAM, a Visual–LiDAR SLAM framework that couples direct LiDAR odometry and loop closures with multi-camera 3D Gaussia

Cited by 1 Source ↗code ↗Scholar ↗

2024

Gradient-based Local Next-best-view Planning for Improved Perception of Targeted Plant Nodes

Akshay K. Burusa, Eldert J. van Henten, Gert Kootstra

ICRA 2024poster

Robots are increasingly used in tomato greenhouses to automate labour-intensive tasks such as selective harvesting and de-leafing. To perform these tasks, robots must be able to accurately and efficiently perceive the plant nodes that need to be cut, despite the high levels of occlusion from other p…

Cited by 4 Source ↗code ↗Scholar ↗