What question did this study set out to answer?

To develop a robotic platform that provides real-time visual and numeric information for assessing CEA farms.

December 10, 2025INMATEH Agricultural EngineeringOpen Access

Design and Experiment of Multi-Purose and Modular Sensor Robotic Platform for Real-Time Assessing and Monitoring of Cea Farms Using Point Cloud, Lidar, RGB and Thermal Imaging

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Authors

ASAlexandru STAN CBCosmin-Karl Banica CGCostin Hedwig GÂNDESCU

Discussion

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Overview

Experimental integration of multi-sensory technology shows improved environment assessment and safety in CEA farms, indicating a new approach to efficiency.

Key Points

To develop a robotic platform that provides real-time visual and numeric information for assessing CEA farms.
Developed a multi-purpose sensor robotic platform integrating LiDAR, point cloud, RGB, and thermal imaging.
Utilized image processing algorithms from OpenCV and conducted experiments with real-time controls via ROS.
Integrated an internet access point to enhance operational capabilities.
The platform achieved six hours of autonomy, demonstrating energy efficiency.
LiDAR mapping achieved a precision of ±7 mm, enhancing operational accuracy.
Implemented multi-sensory integration significantly improved environment assessment and monitoring capabilities.

Cite This Study

STAN et al. (2025) studied this question.

synapsesocial.com/papers/69401b262d562116f28f7a33 https://doi.org/10.35633/inmateh-77-01

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December 10, 2025INMATEH Agricultural EngineeringOpen Access

Design and Experiment of Multi-Purose and Modular Sensor Robotic Platform for Real-Time Assessing and Monitoring of Cea Farms Using Point Cloud, Lidar, RGB and Thermal Imaging

View Full Paper

Ask AI

Bookmark

Authors

ASAlexandru STAN CBCosmin-Karl Banica CGCostin Hedwig GÂNDESCU

Discussion

Member takes

Overview

Experimental integration of multi-sensory technology shows improved environment assessment and safety in CEA farms, indicating a new approach to efficiency.

Key Points

To develop a robotic platform that provides real-time visual and numeric information for assessing CEA farms.
Developed a multi-purpose sensor robotic platform integrating LiDAR, point cloud, RGB, and thermal imaging.
Utilized image processing algorithms from OpenCV and conducted experiments with real-time controls via ROS.
Integrated an internet access point to enhance operational capabilities.
The platform achieved six hours of autonomy, demonstrating energy efficiency.
LiDAR mapping achieved a precision of ±7 mm, enhancing operational accuracy.
Implemented multi-sensory integration significantly improved environment assessment and monitoring capabilities.

Cite This Study

STAN et al. (2025) studied this question.

synapsesocial.com/papers/69401b262d562116f28f7a33 https://doi.org/10.35633/inmateh-77-01

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