All things that move will become autonomous. And all the robots out there are getting smarter, fast! NVIDIA announced its latest initiatives to deliver a suite of perception technologies for developers seeking innovative ways to incorporate cutting-edge computer vision and AI/ML functionality into their ROS-based robotics applications. These new tools reduce time spent developing with ease as they improve performance within your software projects, making them easier than ever before.
NVIDIA and Open Robotics have entered into an agreement to accelerate the performance of ROS 2 on NVIDIA’s Jetson AI platform, as well as GPU-based systems. The two companies will also enable seamless simulation interoperability between Ignition Gazebo’s system and NVIDIA Isaac Sim on Omniverse. Software resulting from this partnership is expected to be released in the spring of 2022.
The Jetson platform is the go-to solution for robotics. It enables high-performance, low latency processing that helps robots be responsive and safe while also being collaborative. Open Robotics will be enhancing the ROS 2 framework to allow for efficient management of data flow and shared memory across GPU processors. This should significantly improve performance when processing applications that rely heavily on high bandwidth, such as lidar sensors in robotic systems. Apart from improved deployment on Jetson, Open Robotics and NVIDIA plan to integrate Ignition Gazebo and NVIDIA Isaac Sim.
By connecting these two simulators together, ROS developers can easily move their robots and environments between Ignition and Isaac Sim to run large-scale simulations. They will be able to use each simulator’s advanced features such as high fidelity dynamics or photorealistic rendering to generate synthetic data when training AI models.
Isaac GEMs have just been released for ROS with significant speedup! This is really exciting news and it’s great that you can try out these new features now.
Isaac GEMs for ROS are hardware accelerated packages that make it easier to build high-performance solutions on the Jetson platform. The focus of these GEMs is improving throughput in image processing and DNN based perception models, which have become increasingly important as roboticists work with their technologies more often than ever before. These GEMs reduce load while providing significant performance gain so developers can spend less time worrying about how much power they’re using or what kind of network connection best suits them at any given moment.
For more details, visit: https://developer.nvidia.com/blog/?p=37657