Leveraging Deep Learning for Object and Position Recognition of Load Carriers for Autonomous Logistics Vehicles
Researchers have developed a deep learning framework to enable autonomous logistics vehicles to detect and estimate the pose of load carriers. The system utilizes a convolutional neural network that processes RGBD data to identify specific landmarks on the carriers. By combining these inferred landmarks with geometric information, the network accurately determines the carrier's position and orientation, proving effective for intralogistics applications. AI