Nvidia going ahead to design autonomous mobile robots to be faster and more agile than ever before.

Artificial intelligence technology is throwing its significant remarks in all aspects of society and business and transforming it to the next level. This, as result, attracted big techs like Nvidia to go ahead to design autonomous mobile robots to be faster and more agile than ever before.

At present, robots possess the capability to do more than just perform tasks. They can learn, adapt, and evolve using capabilities like artificial intelligence, machine learning, computer vision, navigation, and many more. Nvidia has used the power of deep learning to drive this exciting new era of smart embedded robotics—from manufacturing and agriculture to security and home-based healthcare. Nvidia's simulation technologies are being harnessed advance futuristic autonomous mobile robots (AMRs) to be faster and more agile than ever before.

Nvidia's GPU Technology Conference (GTC) did pair of announcements aimed at accelerating the development of AI on the edge and enabling autonomous mobile robots or AMRs. Recent developments at Nvidia will accelerate the creation of artificial intelligence applications, Deepu Talla, Nvidia's vice president of embedded and edge computing. said. "Until a year or two ago, very few companies could build these AI products, because creating an AI model has been very difficult," he said. "We've heard it takes months if not a year-plus in some cases, and then it's…a continuous iterative process. You're not done ever with the AI model."

However, Nvidia has been able to decrease that time considerably by doing three things, Talla said. The first one is including pre-trained models for both computer vision and conversational artificial intelligence. The second is the capacity to generate synthetic data on its new Omniverse platform. Lastly, transfer learning gives Nvidia customers the ability to take those pre-trained models and customize them to a customer's exact specifications by training with "both physical real data and synthetic data," he said.

German research group Fraunhofer Research is making use of Nvidia's technology for its O3dyn platform established to discover and test the manufacturing of autonomous mobile robots by simulating their design and testing their reactions to different environments. The team is anticipating accelerating the speed, agility, and accuracy of these robots, creating high-speed, multi-purpose AMRs for logistics and manufacturing deployment. "We're looking at how we can go as fast and as safely as possible in logistics scenarios," uttered Julian Eber, a robotics and AI researcher at Fraunhofer IML.

Notably, the team is making use of Nvidia's Isaac Sim – a scalable robotics simulation application – to develop 3D, physically error-free digital renderings of the AMRs in various environments, testing their capabilities in each scenario to fine-tune their navigation and speed. Fraunhofer says that Nvidia's tech empowers the company to scan and digitally replicate more than 5,400 robotic parts, as well as customize every one with physically accurate specifications to virtually create and test different iterations of AMRs. These pallet-moving robots reportedly possess capabilities of reaching speeds of up to 30 mph, with artificial intelligence-assisted wheels for navigating through a variety of obstacles. O3dyn also harnesses the NVIDIA Jetson edge artificial intelligence and robotics platform for its camera and sensor inputs. "The omnidirectional dynamics is very unique, and there's nothing like this that we know of in the market," stated Sören Kerner, head of artificial intelligence and autonomous systems at Fraunhofer IML.

The team also declared that the project is minimizing the gap between sim technology and real life, meaning that digital renderings of situations are becoming increasingly inch-perfect allowing engineers to bring robots from concept to deployment more quickly than ever before – a concept Fraunhofer calls simulation-based artificial intelligence. "This is important for the future of logistics," said Kerner. "We want to have as many people as possible work on the localization, navigation, and artificial intelligence of these kinds of dynamic robots in simulation."