Design and Research of Intelligent Robot 3D Recognition Processing System

With the continuous advancement of artificial intelligence technology, intelligent robots are increasingly and extensively utilized in industrial production, daily life, as well as detection and security. This paper presents the design and research of a 3D recognition and processing system for intelligent robots, with the aim of enhancing the autonomous cognition and decision-making ability of robots in complex environments. Firstly, the system is based on advanced 3D sensing technology, through the combination of multi-line LiDAR for assisted acquisition of point cloud data and stereo vision. Subsequently, a deep learning network architecture of global features and local scale features is designed for the feature extraction and classification of point cloud data. Finally, through training and optimizing the model, accurate 3D object recognition is achieved. The experimental results demonstrate that the classification accuracy of the system on the training set and the test set has reached a high level, and it can well recognize different categories of three-dimensional objects.