Example use of machine learning with automatically guided vehicles (AGVs).
Texas Instruments has a new article by Pekka Varis on Maximizing machine-learning inference at the edge. It takes a look at the use of machine learning to solve problems of AGV navigation in warehouses where there’s reduced navigation space as warehouse density increases, the requirement to classify objects on the factory floor and to share the space with humans.
The article gives a summary of the process of machine learning including collecting data, training and inference. Inference, the use of machine learning in the actual situation, is the main focus of the article in that it has to run quickly in order to determine the AGV’s path, other vehicles and people in real time. The image at the top shows the AGV’s path (green), another vehicle (blue) and people (red).