Vision-based working area boundary detection system and method, and machine equipment

Abstract

The invention discloses a vision-based working area boundary detection system, method and machine equipment. When implementing the solution, we firstly train the constructed neural network model based on the training data set, extract and learn the features of the corresponding working area. Next, the neural network after training and learning is employed to perform real-time image semantic segmentation on the collected video images based on the extracted features, thereby perceiving the environment and identifying the boundaries of the working area. The solution provided by the present invention is based on neural network technology, and can efficiently identify the boundary of the working area through the extraction and learning of the features of the working area in the early stage, and has strong robustness to environmental perturbation such as lighting.

Dependencies are inferred from the claim text.