An Intelligent Water-Saving Irrigation System Based on Multi-Sensor Fusion and Visual Servoing Control

• URL: http://arxiv.org/abs/2510.23003v1
• Date: Mon, 27 Oct 2025 04:43:20 GMT
• Title: An Intelligent Water-Saving Irrigation System Based on Multi-Sensor Fusion and Visual Servoing Control
• Authors: ZhengKai Huang, YiKun Wang, ChenYu Hui, XiaoCheng,
• Abstract summary: This paper introduces an intelligent water-saving irrigation system designed to address critical challenges in precision agriculture.<n>The system integrates advanced computer vision, robotic control, and real-time stabilization technologies via a multi-sensor fusion approach.
• Score: 3.055831281462442
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces an intelligent water-saving irrigation system designed to address critical challenges in precision agriculture, such as inefficient water use and poor terrain adaptability. The system integrates advanced computer vision, robotic control, and real-time stabilization technologies via a multi-sensor fusion approach. A lightweight YOLO model, deployed on an embedded vision processor (K210), enables real-time plant container detection with over 96% accuracy under varying lighting conditions. A simplified hand-eye calibration algorithm-designed for 'handheld camera' robot arm configurations-ensures that the end effector can be precisely positioned, with a success rate exceeding 90%. The active leveling system, driven by the STM32F103ZET6 main control chip and JY901S inertial measurement data, can stabilize the irrigation platform on slopes up to 10 degrees, with a response time of 1.8 seconds. Experimental results across three simulated agricultural environments (standard greenhouse, hilly terrain, complex lighting) demonstrate a 30-50% reduction in water consumption compared to conventional flood irrigation, with water use efficiency exceeding 92% in all test cases.

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