ReviewCurrent robotics reports2022
Review of Current Robotic Approaches for Precision Weed Management.
Review in Current robotics reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- A Review of Robotic Weeding Modalities for Site-Specific Weed Management.Sensors (Basel, Switzerland) · 2026Review
- The Invasive Mechanism and Impact ofPlants (Basel, Switzerland) · 2025Review
- Agronomic and Technical Evaluation of Herbicide Spot Spraying in Maize Based on High-Resolution Aerial Weed Maps-An On-Farm Trial.Plants (Basel, Switzerland) · 2024Article
- Laser weeding: opportunities and challenges for couch grass (Elymus repens (L.) Gould) control.Scientific reports · 2024Article
- Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials.Environmental science & technology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose of Review: The goal of this review is to provide an overview of current robotic approaches to precision weed management. This includes an investigation into applications within this field during the past 5 years, identifying which major technical areas currently preclude more widespread use, and which key topics will drive future development and utilisation. Recent Findings: Studies combining computer vision with traditional machine learning and deep learning are driving progress in weed detection and robotic approaches to mechanical weeding. Integrating key technologies for perception, decision-making, and control, autonomous weeding robots are emerging quickly. These effectively save effort while reducing environmental pollution caused by pesticide use. Summary: This review assesses different weed detection methods and weeder robots used in precision weed management and summarises the trends in this area in recent years. The limitations of current systems are discussed, and ideas for future research directions are proposed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.