51 citations · 76 across the 13 of their papers we have counts for
13 papers
Enhancing annotations for 5D apple pose estimation through 3D Gaussian Splatting (3DGS)
Robert van de Ven, Trim Bresilla, Bram Nelissen +3
Automating tasks in orchards is challenging because of the large amount of variation in the environment and occlusions. One of the challenges is apple pose estimation, where key po…
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…
Lameness detection in dairy cows using pose estimation and bidirectional LSTMs
Helena Russello, Rik van der Tol, Eldert J. van Henten +1
This study presents a lameness detection approach that combines pose estimation and Bidirectional Long-Short-Term Memory (BLSTM) neural networks. Combining pose-estimation and BLST…
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…
SSL-NBV: A Self-Supervised-Learning-Based Next-Best-View algorithm for Efficient 3D Plant Reconstruction by a Robot
Jianchao Ci, Eldert J. van Henten, Xin Wang +2
The 3D reconstruction of plants is challenging due to their complex shape causing many occlusions. Next-Best-View (NBV) methods address this by iteratively selecting new viewpoints…
Improved detection of discarded fish species through BoxAL active learning
Maria Sokolova, Pieter M. Blok, Angelo Mencarelli +3
In recent years, powerful data-driven deep-learning techniques have been developed and applied for automated catch registration. However, these methods are dependent on the labelle…
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…
A comparison between single-stage and two-stage 3D tracking algorithms for greenhouse robotics
David Rapado-Rincon, Akshay K. Burusa, Eldert J. van Henten +1
With 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…
Video-based automatic lameness detection of dairy cows using pose estimation and multiple locomotion traits
Helena Russello, Rik van der Tol, Menno Holzhauer +2
This study presents an automated lameness detection system that uses deep-learning image processing techniques to extract multiple locomotion traits associated with lameness. Using…
3D Pose Estimation of Tomato Peduncle Nodes using Deep Keypoint Detection and Point Cloud
Jianchao Ci, Xin Wang, David Rapado-Rincón +2
Greenhouse production of fruits and vegetables in developed countries is challenged by labor 12 scarcity and high labor costs. Robots offer a good solution for sustainable and cost…
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…
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,…