AI in Smart Warehouses Smart warehouses are using AI-at-the-edge technologies to automate inventory processes, simplify general package handling, and optimize real estate when receiving orders and sending packages to other distribution centers. Developers can leverage the different components of building, training, and deploying algorithms for inference at the edge. Learn how to bring agility and flexibility to distribution centers with AI Explore AI computer vision applications at the edge for retail
Robots for Package Handling Store associates are the face of retail organizations. To maximize time with customers, retailers are working to reduce the time they spend on non-customer-facing tasks, such as inventory counts. Large retailers are using robotics technology to unload and sort items based on priority and department, check stock levels, correct shelf locations, and ensure price accuracy. To resolve throughput challenges from the scale and variety of products, companies are using edge computing to detect, classify, estimate the size of, and position packages, automatically adjust the speed of conveyors and optimize mechanical sorting. This helps to minimize product damage and machine downtime. See how robots are tracking inventory at Lowe’s
Route Optimization for Large Distribution Networks Warehouse and manufacturing centers are solving the enormous complexities of product flows with AI-powered robots. These robots utilize powerful deep neural networks for perception, segmentation, and pose estimation to perceive their environment, detect objects, navigate autonomously, and move objects. Market leaders are widening their competitive advantage with increased throughput, per-order customization, and differentiated customer experiences. The NVIDIA Isaac™ robotics platform allows BMW Group to easily manage new models and configurations to meet customer demand, using AI technology to innovate factory logistics. With this approach, they can produce high-quality, highly custom-configured cars more rapidly on the same production line. See how BMW Group is redefining factory logistics
Last-Mile Delivery Solutions Several factors can impact the last mile of delivery, including traffic, construction, and weather. Using real-time data from a variety of sources—from GPS data to weather forecasts—routes can be optimized, which can significantly impact fuel, personnel, and other overhead costs. Beyond that, by using NVIDIA GPU-powered smart solutions to optimize routes, carriers can provide more accurate delivery windows, improving the level of service provided to customers. This instills a higher degree of trust, which matters when customers have an array of options for sending and receiving important parcels. NVIDIA ReOpt™ empowers developers to leverage larger datasets and faster processing to optimize last-mile delivery with new capabilities like dynamic rerouting, simulations, and sub-second response times in the warehouse and on the road. Learn about the world's first socially aware delivery robot