Robotics receives shock from open Robotics-Nvidia partnership
Nvidia and Open Robotics have 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 launched 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 primarily targets traditional CPU compute models. In recent years, however, Nvidia has pioneered heterogeneous computing and AI 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) to simplify the development and deployment of AI models, and Omniverse Isaac Sim for synthetic data generation and robotic simulation. Both environments are open to developers and provide valuable code, models, datasets, and simulation resources. Now the two can be combined in Nvidia’s Omniverse collaborative development environment to allow developers to develop everything from the physical robot to synthetic data sets to train the robot simultaneously.
For ROS developers, this opens up a world of possibilities. Integrating ROS into the Nvidia environment gives the developer the ability to leverage offload / acceleration engines such as GPU, shared memory, and predefined hardware acceleration algorithms that Nvidia calls Isaac Gems. So far, Nvidia offers 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 increase in offload performance depends on the specific algorithm, but Nvidia expects some to result in an order of magnitude performance improvement over the same implementation on a processor. Additionally, Isaac Sim supports 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 predefined algorithms combined with the synthetic data allow even the most novice developers or startups to develop robotic platforms quickly.
ROS developers looking to add AI technologies to their products will also be able to take advantage of other Nvidia SDKs, such as Fleet Command for remote system management, Riva for conversational AI, and Deepstream for streaming analytics. video. Most importantly, from Tirias Research’s perspective, the ability to take advantage of the Omniverse environment, which enables multiple simultaneous users with seamless interaction between tools, and the massive amounts of new data and learning models. automatic (ML) developed by Nvidia.
Although Nvidia has SDKs for various applications, such as Isaac for robotics, Clara for health, and Drive for autonomous vehicles, the ML models for each of these segments increasingly overlap. Discussing this point, Nvidia’s General Manager of Robotics, Murali Gopalakrishna, Mr. Gopalakrishna indicated that there is considerable intersection in the development of SDKs and models for many applications. According to Mr. Gopalakrishna, âthe only difference is in the data; the decisions are always the same. As a result, advancements in one market or application typically benefit multiple markets and applications.
According to data from Statista, the robotics market is expected to grow at more than 25% per year, an increase from around 20% before COVID. COVID is pushing the use of robotics in everything from healthcare and manufacturing to agriculture and food delivery. Leveraging advancements in AI, sensors, wireless communications (5G), and semiconductor technology, robotics is rapidly becoming mainstream in society. By 2025, the global robotics market will reach $ 210 billion, but this is a fraction of the value of the products and services that will be generated by robotics. After evaluating various development platforms and tools, I can attest to the value of the resources that the Nvidia Isaac and ROS platforms offer to developers. Both make it easy for developers to start 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 union of the two environments also brings together the two largest robotics development communities, both focused on open source collaboration.