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Agriculture industries often face challenges in manual tasks such asplanting, harvesting, fertilizing, and detection, which can be time consumingand prone to errors. The "Agricultural Robotic System" project addresses theseissues through a modular design that integrates advanced visual, speechrecognition, and robotic technologies. This system is comprised of separate butinterconnected modules for vision detection and speech recognition, creating aflexible and adaptable solution. The vision detection module uses computervision techniques, trained on YOLOv5 and deployed on the Jetson Nano inTensorRT format, to accurately detect and identify different items. A roboticarm module then precisely controls the picking up of seedlings or seeds, andarranges them in specific locations. The speech recognition module enhancesintelligent human robot interaction, allowing for efficient and intuitivecontrol of the system. This modular approach improves the efficiency andaccuracy of agricultural tasks, demonstrating the potential of robotics in theagricultural industry.

Agricultural Robotic System: The Automation of Detection and Speech Control