Evidence map›Paper›PMID 36721646›Full record

ReviewJournal of intelligent & robotic systems2023

A Survey of Robotic Harvesting Systems and Enabling Technologies.

Leonidas Droukas, Zoe Doulgeri, Nikolaos L Tsakiridis, Dimitra Triantafyllou, Ioannis Kleitsiotis, Ioannis Mariolis, Dimitrios Giakoumis, Dimitrios Tzovaras, Dimitrios Kateris, Dionysis Bochtis

Abstract readReview
In one paragraph

Review in Journal of intelligent & robotic systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Gripping Success Metric for Robotic Fruit Harvesting.Sensors (Basel, Switzerland) · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Leonidas DroukasDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki (AUTH), Thessaloniki, 54124 Greece.
Zoe DoulgeriDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki (AUTH), Thessaloniki, 54124 Greece.
Nikolaos L TsakiridisDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki (AUTH), Thessaloniki, 54124 Greece.
Dimitra TriantafyllouInformation Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001 Greece.
Ioannis KleitsiotisInformation Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001 Greece.
Ioannis MariolisInformation Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001 Greece.
Dimitrios GiakoumisInformation Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001 Greece.
Dimitrios TzovarasInformation Technologies Institute (ITI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001 Greece.
Dimitrios KaterisInstitute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Volos, 38333 Greece.
Dionysis BochtisInstitute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Volos, 38333 Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related challenges. Health monitoring, yield estimation, water status inspection, seed planting and weed removal are frequently encountered tasks. Regarding robotic harvesting, apples, strawberries, tomatoes and sweet peppers are mainly the crops considered in publications, research projects and commercial products. The reported harvesting agricultural robotic solutions, typically consist of a mobile platform, a single robotic arm/manipulator and various navigation/vision systems. This paper reviews reported development of specific functionalities and hardware, typically required by an operating agricultural robot harvester; they include (a) vision systems, (b) motion planning/navigation methodologies (for the robotic platform and/or arm), (c) Human-Robot-Interaction (HRI) strategies with 3D visualization, (d) system operation planning & grasping strategies and (e) robotic end-effector/gripper design. Clearly, automated agriculture and specifically autonomous harvesting via robotic systems is a research area that remains wide open, offering several challenges where new contributions can be made.

Indexed as

Agricultural functionalitiesAutomated agricultureRobotic harvestingState-of-art review

Identifiers

PMID36721646
PMCPMC9881528

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.