Leveraging Deep Learning for Object and Position Recognition of Load Carriers for Autonomous Logistics Vehicles (opens in new tab)
This work explores the use of artificial intelligence in mobile robotics to achieve autonomous detection and pose estimation of load carriers for automated pickup. A deep neural network is designed to recognize predefined landmarks on the carrier from RGBD data; these landmarks are then used to compute the carrier's pose. The network operates directly on RGBD images to estimate landmark positions, which form the basis for determining the carrier...
Read the original article