7 papers · 1 filter
AgriGS-SLAM: Orchard Mapping Across Seasons via Multi-View Gaussian Splatting SLAM
Mirko Usuelli, David Rapado-Rincon, Gert Kootstra +1
Autonomous robots in orchards require real-time 3D scene understanding despite repetitive row geometry, seasonal appearance changes, and wind-driven foliage motion. We present Agri…
Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards
David Rapado-Rincon, Gert Kootstra
Accurate mapping of individual trees is an important component for precision agriculture in orchards, as it allows autonomous robots to perform tasks like targeted operations or in…
UAV-based path planning for efficient localization of non-uniformly distributed weeds using prior knowledge: A reinforcement-learning approach
Rick van Essen, Eldert van Henten, Gert Kootstra
UAVs are becoming popular in agriculture, however, they usually use time-consuming row-by-row flight paths. This paper presents a deep-reinforcement-learning-based approach for pat…
DualLQR: Efficient Grasping of Oscillating Apples using Task Parameterized Learning from Demonstration
Robert van de Ven, Ard Nieuwenhuizen, Eldert J. van Henten +1
Learning from Demonstration offers great potential for robots to learn to perform agricultural tasks, specifically selective harvesting. One of the challenges is that the target fr…
MOT-DETR: 3D Single Shot Detection and Tracking with Transformers to build 3D representations for Agro-Food Robots
David Rapado-Rincon, Henk Nap, Katarina Smolenova +2
In the current demand for automation in the agro-food industry, accurately detecting and localizing relevant objects in 3D is essential for successful robotic operations. However,…
Gradient-based Local Next-best-view Planning for Improved Perception of Targeted Plant Nodes
Akshay K. Burusa, Eldert J. van Henten, Gert Kootstra
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 ac…