51 citations · 201 across the 13 of their papers we have counts for
14 papers
LettuceVisSim: A Simulator That Generates Lettuce Image Time-series for Vision-Based Reinforcement Learning
Ziye Zhu, Bert van 't Ooster, Congcong Sun +2
Vision-based reinforcement learning holds strong potential for decision-making in controlled environment agriculture (CEA). However, its development is hindered by the scarcity of…
Improving greenhouse fruit-production control by integrating reinforcement learning into short-horizon model predictive control
Bart van Laatum, Salim Msaad, Eldert J. van Henten +2
Greenhouse fruit-production control aims to maximize the economic performance (fruit revenue minus operating costs) while operating within system constraints under external weather…
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…
A drone that learns to efficiently find non-uniformly distributed objects in agricultural fields: from simulation to the real world
Rick van Essen, Eldert van Henten, Gert Kootstra
Drones are promising for data collection in precision agriculture but are limited by battery capacity. Drone paths are usually planned using full coverage planners, even though thi…
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…
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…
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,…
MinkSORT: A 3D deep feature extractor using sparse convolutions to improve 3D multi-object tracking in greenhouse tomato plants
David Rapado-Rincon, Eldert J. van Henten, Gert Kootstra
The agro-food industry is turning to robots to address the challenge of labour shortage. However, agro-food environments pose difficulties for robots due to high variation and occl…
Reinforcement Learning Versus Model Predictive Control on Greenhouse Climate Control
Bernardo Morcego, Wenjie Yin, Sjoerd Boersma +3
Greenhouse is an important protected horticulture system for feeding the world with enough fresh food. However, to maintain an ideal growing climate in a greenhouse requires resour…
Development and evaluation of automated localisation and reconstruction of all fruits on tomato plants in a greenhouse based on multi-view perception and 3D multi-object tracking
David Rapado Rincon, Eldert J. van Henten, Gert Kootstra
The ability to accurately represent and localise relevant objects is essential for robots to carry out tasks effectively. Traditional approaches, where robots simply capture an ima…
Attention-driven Next-best-view Planning for Efficient Reconstruction of Plants and Targeted Plant Parts
Akshay K. Burusa, Eldert J. van Henten, Gert Kootstra
Robots in tomato greenhouses need to perceive the plant and plant parts accurately to automate monitoring, harvesting, and de-leafing tasks. Existing perception systems struggle wi…
Active learning with MaskAL reduces annotation effort for training Mask R-CNN
Pieter M. Blok, Gert Kootstra, Hakim Elchaoui Elghor +3
The generalisation performance of a convolutional neural network (CNN) is influenced by the quantity, quality, and variety of the training images. Training images must be annotated…