papers

Publications (10)

cs.RO2022

Towards Autonomous Visual Navigation in Arable Fields

Alireza Ahmadi, Michael Halstead, Chris McCool

Autonomous navigation of a robot in agricultural fields is essential for every task from crop monitoring to weed management and fertilizer application. Many current approaches rely…

cs.RO2024

BonnBot-I: A Precise Weed Management and Crop Monitoring Platform

Alireza Ahmadi, Michael Halstead, Chris McCool

Cultivation and weeding are two of the primary tasks performed by farmers today. A recent challenge for weeding is the desire to reduce herbicide and pesticide treatments while mai…

cs.CV2021

Virtual Temporal Samples for Recurrent Neural Networks: applied to semantic segmentation in agriculture

Alireza Ahmadi, Michael Halstead, Chris McCool

This paper explores the potential for performing temporal semantic segmentation in the context of agricultural robotics without temporally labelled data. We achieve this by proposi…

cs.CV2026

Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels

Michael Halstead, Esra Guclu, Mohamed Farag +7

The paper introduces two new datasets of tomato plants captured by a robot—still images (BUTom21) and video sequences (BUTom-ST21)—with pixel‑level annotations for fruit detection,…

#tomato phenotyping#image dataset#video dataset#semantic segmentation
cs.RO2024

BonnBot-I Plus: A Bio-diversity Aware Precise Weed Management Robotic Platform

Alireza Ahmadi, Michael Halstead, Claus Smitt +1

In this article, we focus on the critical tasks of plant protection in arable farms, addressing a modern challenge in agriculture: integrating ecological considerations into the op…

cs.RO2021

PATHoBot: A Robot for Glasshouse Crop Phenotyping and Intervention

Claus Smitt, Michael Halstead, Tobias Zaenker +2

We present PATHoBot an autonomous crop surveying and intervention robot for glasshouse environments. The aim of this platform is to autonomously gather high quality data and also e…

cs.RO2023

PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics

Claus Smitt, Michael Halstead, Patrick Zimmer +4

Precise scene understanding is key for most robot monitoring and intervention tasks in agriculture. In this work we present PAg-NeRF which is a novel NeRF-based system that enables…

cs.CV2025

A Dataset and Benchmark for Shape Completion of Fruits for Agricultural Robotics

Federico Magistri, Thomas Läbe, Elias Marks +9

As the world population is expected to reach 10 billion by 2050, our agricultural production system needs to double its productivity despite a decline of human workforce in the agr…

cs.CV2023

Panoptic One-Click Segmentation: Applied to Agricultural Data

Patrick Zimmer, Michael Halstead, Chris McCool

In weed control, precision agriculture can help to greatly reduce the use of herbicides, resulting in both economical and ecological benefits. A key element is the ability to locat…

cs.RO2022

Explicitly incorporating spatial information to recurrent networks for agriculture

Claus Smitt, Michael Halstead, Alireza Ahmadi +1

In agriculture, the majority of vision systems perform still image classification. Yet, recent work has highlighted the potential of spatial and temporal cues as a rich source of i…