AI can deal with a wide variety of scenarios and situations, since the logic is based on real existing data and is not manually programmed. With the tools from Data Spree, the AI can be flexibly expanded at any time and can be trained on new, definable objects or classes. In this way, complex orientation patterns for AGVs can be implemented that were inconceivable with conventional methods.
Traditional algorithms - complex, inflexible and expensive
Classic image processing has to be programmed from scratch in a very complex process. In this process, algorithms are developed manually by experts, which requires a lot of know-how and time. These classically programmed algorithms work according to hand-made rules and decision criteria. Risks arise if there are deviations from these rules in operation. These deviations can be, for example, changing lighting conditions, environmental parameters, changes in the routes, procedures or processes. By means of training with real environmental data, Artificial Intelligence can correctly assess a wide variety of situations and environmental changes and react correctly.
That is why logistics must use Artificial Intelligence (AI) in the future
With AI-based image processing, as shown in the example, autonomous vehicles can interpret complex work situations and processes better and make human-machine interaction safer. Depending on the training, AI networks can be trained on various obstacles and objects, for example packages, pallets, high racks, containers, etc. This opens up limitless possibilities for autonomous vehicles, but also for collaborative robots or automation in general.
Smart processes automated with AI will be a key element in modern logistics in the future. Thanks to Artificial Intelligence, the many lines of programming code will be a thing of the past. Automated processes for transport, counting tasks or sorting can be implemented quickly and securely with AI-based image processing and the corresponding tools from Data Spree. An insight into this new type of image processing is particularly worthwhile in logistics, where time and costs are the decisive factors for success.