Nvidia and Open Robotics announced a partnership to enhance the ROS 2 (Robot Operating System) development suite. The partnership essentially combines the two most powerful robotics development environments and the two largest groups of robotics developers.
First released in 2010, ROS has been a key open-source platform for robotics developers supported by various companies in a variety of industries and government research organizations like DARPA and NASA. While the platform has continued to grow and includes the Ignition simulation environment, it has been primarily targeting traditional CPU computing models. Over the past several years, however, Nvidia has pioneered heterogeneous and AI computing for IoT and edge applications through the development of its Jetson platforms, software development kits (SDKs) like Isaac for robotics, toolkits like Nvidia TAO (Train, Adapt, and Optimize) for simplifying AI model development and deployment, and Omniverse Isaac Sim for synthetic data generation and robotics simulation. Both environments are open to developers, provide valuable code, models, data sets, and simulation resources. Now the two can be combined into Nvidia’s Omniverse collaborative development environment to allow developers to simultaneously develop everything from the physical robot to synthetic data sets to train the robot.
For the ROS developers, this opens a world of possibilities. Pulling ROS into the Nvidia environment offers the developer the ability to leverage offload/acceleration engines like a GPU, shared memory, and predesigned hardware acceleration algorithms Nvidia calls Isaac Gems. Thus far, Nvidia is offering three Gems for image processing and DNN-based perception models, including SGM Stereo Disparity and Point Cloud, Color Space Conversion and Lens Distortion Correction, and AprilTags Detection. The performance lift from offloading depends on the specific algorithm, but Nvidia expects that some will result in an order of magnitude improvement in performance versus the same implementation on a CPU. In addition, the Isaac Sim includes support for ROS and ROS2 algorithms, including ROS April Tag, ROS Stereo Camera, ROS Services, Movelt Motion Planning Framework, Native Python ROS Usage, and ROS2 Navigation. The Isaac Sim can also be used to generate synthetic data to train and test perception models. The predesigned algorithms combined the synthetic data allow even the most novice developer or startup to quickly develop robotic platforms.
ROS developers seeking to add AI technologies to their products will also be able to leverage other Nvidia SDKs, such as Fleet Command for remote system management, Riva for conversational AI, and Deepstream for video streaming analytics. Most importantly, from Tirias Research’s perspective is the ability to leverage the Omniverse environment, which allows multiple simultaneous users with seamless interaction between tools, and the massive amounts of new data and machine learning (ML) models being developed by Nvidia.
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Although, Nvidia has SDKs for various applications, such as Isaac for robotics, Clara for healthcare, and Drive for autonomous vehicles, the ML models for each of these segments are increasingly overlapping. When discussing this point the Nvidia’s General Manager of Robotics Murali Gopalakrishna, Mr. Gopalakrishna indicated that there is considerable crossover in the development of the SDKs and models for many of the applications. According to Mr. Gopalakrishna “the only difference is the data; the decisions are still the same.” As a result, the advances in one market or application typically benefits multiple markets and applications.
According to data from Statista, the robotics market is projected to grow at over a 25% rate annually, an increase from approximately 20% prior to COVID. COVID is pushing the use of robotics in everything from healthcare and manufacturing to agriculture and food delivery. Leveraging the advancements in AI, sensors, wireless communications (5G), and semiconductor technology, robotics is rapidly moving into the mainstream of society. By 2025, the global robotics market will reach $210 billion, but that is a fraction of the value of the products and services that will be generated by robotics. Having evaluated various development platforms and tools, I can attest to the value of the resources that the Nvidia Isaac and ROS platforms offer developers. Both make it easy for developers to begin developing new robotic platforms but the combination of the two, for lack of a better way to describe it, democratizes robotic development and AI for robotics. The joining of the two environments also brings together the two largest robotics develop communities, both focused on open-source collaboration.