Robots for agricultural harvesting

[taobotics]

Agricultural robots are designed to perform various tasks on farms, such as planting, harvesting, and sorting crops. Agricultural robots can be autonomous or semi-autonomous and are often equipped with sensors, cameras, and other technologies to help them navigate and perform their tasks efficiently.
Examples of agricultural robots include robotic harvesters, weeders, and fruit pickers. These robots can help farmers increase their productivity and efficiency and can also reduce the amount of labour required to maintain a farm.
The smart agricultural harvesting robot system is based on HandsFree robots and open-source systems, which enable robots to capture images in real time through cameras in agricultural production. With the support of deep learning technology, they can accurately identify and harvest, continuously update data, accumulate learning, and become increasingly "smart".
The intelligent agricultural harvesting robot system utilizes the LiDAR of the mobile chassis to obtain object position information in an unstructured environment, and converts the position information into a navigation map of the unstructured environment through the SLAM algorithm. Subsequently, the robot system obtains image data through the camera, processes the image data containing apples through deep learning algorithms, and calculates the approximate position of the apples. Subsequently, the robot compares the current position with the apple position and sends motion instructions to the moving chassis, causing the robot to move near the apple. Next, utilizing the position judgment ability of the depth camera, combined with visual recognition algorithms, real-time error correction is achieved through visual servo algorithms to control the robotic arm to grasp apples.