Smart agriculture is experiencing rapid transformation through innovative Agritech solutions. Robotic Arms (RAs) and Sensor-equipped Wearable Gloves (SWGs) are critical tools for performing high-precision tasks in controlled environments like hydroponic greenhouses. Digital Twin (DT) technology further enhances these systems, enabling real-time monitoring, dynamic adaptation, and predictive maintenance, thus ensuring optimal efficiency and cost savings. This paper investigates the integration of DT technology into a hydroponic greenhouse to facilitate remote control of a RA using a SWG. We have developed a DT framework that synchronizes physical and digital environments for real-time motion planning and monitoring. Our system architecture aims to demonstrate the potential of DTs in agriculture, allowing tasks to be performed in three modes: Real-to-Digital (updating the DT with real-world data), Digital-to-Real (executing commands from the digital model in the physical world), and Digital-to-Digital (simulating scenarios to optimize performance). Experimental validation highlights the system's performance, focusing on communication and computing delays and their impact on real-time operations.

Digital Twin for Remote Control of Robotic Arm via Wearable Glove in Smart Agriculture

Bua C.;Borgianni L.;Giordano S.
2025-01-01

Abstract

Smart agriculture is experiencing rapid transformation through innovative Agritech solutions. Robotic Arms (RAs) and Sensor-equipped Wearable Gloves (SWGs) are critical tools for performing high-precision tasks in controlled environments like hydroponic greenhouses. Digital Twin (DT) technology further enhances these systems, enabling real-time monitoring, dynamic adaptation, and predictive maintenance, thus ensuring optimal efficiency and cost savings. This paper investigates the integration of DT technology into a hydroponic greenhouse to facilitate remote control of a RA using a SWG. We have developed a DT framework that synchronizes physical and digital environments for real-time motion planning and monitoring. Our system architecture aims to demonstrate the potential of DTs in agriculture, allowing tasks to be performed in three modes: Real-to-Digital (updating the DT with real-world data), Digital-to-Real (executing commands from the digital model in the physical world), and Digital-to-Digital (simulating scenarios to optimize performance). Experimental validation highlights the system's performance, focusing on communication and computing delays and their impact on real-time operations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1345138
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