Human–Robot Interaction in Agriculture: A Systematic Review

Benos, Lefteris; Moysiadis, Vasileios; Kateris, Dimitrios; Tagarakis, Aristotelis C.; Busato, Patrizia; Pearson, Simon; Bochtis, Dionysis

doi:10.3390/s23156776

Cited by 18 publications

(5 citation statements)

References 91 publications

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“…Remote sensing and IoT are both essential to the collection and processing of data, although they function on different scales and have different goals. Robust remote sensing data streams are necessary to fine-tune and enhance robot algorithms for increased efficacy [75]. Largescale coverage is offered by remote sensing, which offers a comprehensive picture of changing environmental conditions, weather patterns, and landscapes.…”

Section: Human-machine Collaboration and Upskillingmentioning

confidence: 99%

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Victor,

Maddikunta,

Mary

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Agriculture can be regarded as the backbone of human civilization. As technology evolved, the synergy between agriculture and remote sensing has brought about a paradigm shift, thereby entirely revolutionizing the traditional agricultural practices. Nevertheless, the adoption of remote sensing technologies in agriculture face various challenges in terms of limited spatial and temporal coverage, high cloud cover, low data quality and so on. Industry 5.0 marks a new era in the industrial revolution, where humans and machines collaborate closely, leveraging their distinct capabilities, thereby enhancing the decision making capabilities, sustainability and resilience. This paper provides a comprehensive survey on remote sensing technologies and related aspects in dealing with the various agricultural practices in the Industry 5.0 (I5.0) era. We also elaborately discuss the various applications pertaining to I5.0enabled remote sensing for agriculture. Finally, we discuss several challenges and issues related to the integration of I5.0 technologies in agricultural remote sensing. This comprehensive survey on remote sensing for agriculture in Industry 5.0 era offers valuable insights into the current state, challenges, and potential advancements in the integration of remote sensing technologies and Industry 5.0 principles in agriculture, thus paving the way for future research, development, and implementation strategies in this domain.

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Section: Human-machine Collaboration and Upskillingmentioning

confidence: 99%

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Victor,

Maddikunta,

Mary

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…In the present review study, a sequence of six key steps was employed, mirroring relevant scholarly practices [46,47]:…”

Section: Essential Systematic Review Stepsmentioning

confidence: 99%

Digital Twins in Agriculture and Forestry: A Review

Tagarakis,

Benos,

Kyriakarakos

et al. 2024

Sensors

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Digital twins aim to optimize practices implemented in various sectors by bridging the gap between the physical and digital worlds. Focusing on open-field agriculture, livestock farming, and forestry and reviewing the current applications in these domains, this paper reveals the multifaceted roles of digital twins. Diverse key aspects are examined, including digital twin integration and maturity level, means of data acquisition, technological capabilities, and commonly used input and output features. Through the prism of four primary research questions, the state of the art of digital twins, the extent of their achieved integration, and an overview of the critical issues and potential advancements are provided in the landscape of the sectors under consideration. The paper concludes that in spite of the remarkable progress, there is a long way towards achieving full digital twin. Challenges still persist, while the key factor seems to be the integration of expert knowledge from different stakeholders. In light of the constraints identified in the review analysis, a new sector-specific definition for digital twins is also suggested to align with the distinctive characteristics of intricate biotic and abiotic systems. This research is anticipated to serve as a useful reference for stakeholders, enhancing awareness of the considerable benefits associated with digital twins and promoting a more systematic and comprehensive exploration of this transformative topic.

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“…[ 11 ] Agriculture utilizes HRI for targeted crop recognition, aiming to enhance agricultural adaptability and efficiency. [ 12 ] In smart manufacturing, the aim is to integrate AI in a human‐centric way to improve capabilities and create personalized products, a step toward Industry 5.0. [ 2 ] This paper focuses on industrial HRI, specifically multimodal technologies.…”

Section: Overviewmentioning

confidence: 99%

Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey

Wang,

Zheng,

et al. 2023

Advanced Intelligent Systems

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Human–robot interaction (HRI) has escalated in notability in recent years, and multimodal communication and control strategies are necessitated to guarantee a secure, efficient, and intelligent HRI experience. In spite of the considerable focus on multimodal HRI, comprehensive disquisitions delineating various modalities and intricately analyzing their combinations remain elusive, consequently limiting holistic understanding and future advancements. This article aspires to bridge this inadequacy by conducting a profound exploration of multimodal HRI, predominantly concentrating on four principal modalities: vision, auditory and language, haptics, and physiological sensing. An extensive review encapsulating algorithmic dissection, interface devices, and applicative dimensions forms part of this discourse. This manuscript distinctively combines multimodal HRI with cognitive science, deeply probing into the three dimensions, perception, cognition, and action, thereby demystifying algorithms intrinsic to multimodal HRI. Finally, it accentuates the empirical challenges and contours preemptive trajectories for multimodal HRI in human‐centric smart manufacturing.

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Human–Robot Interaction in Agriculture: A Systematic Review

Cited by 18 publications

References 91 publications

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Remote Sensing for Agriculture in the Era of Industry 5.0—A Survey

Digital Twins in Agriculture and Forestry: A Review

Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey

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