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Introduction：

On July 2, the "NVIDIA Robotics Open Course"Completed successfully.Shu Jiaming, Director of Solutions Architecture, NVIDIAby"NVIDIA Isaac accelerates robot 3D visual perception and robotic arm trajectory planning》 was a live broadcast on the topic.

The era of AI robotics has arrived. Based on the NVIDIA Isaac robotics platform, NVIDIA is continuously leveraging the latest generative AI and advanced simulation technologies to accelerate the development of AI robotics technology.

Since the beginning of this year, the NVIDIA Isaac robotics platform has undergone major updates. At GTC 2024 in March, NVIDIA released a series of basic models, robotics tools, and GPU acceleration libraries such as Isaac Perceptor and Isaac Manipulator. In June of this year, the latest NVIDIA Isaac Sim 4.0 version was officially available for download.

Isaac Perceptor for AMR visual AI provides developers with multi-camera 360-degree vision capabilities. This feature can enhance the 3D surround vision capabilities and spatial hierarchy of AMRs, helping AMRs improve work efficiency while also enhancing obstacle avoidance accuracy and ensuring worker safety.

Isaac Manipulator provides flexible and modular AI capabilities for the robotic arm. Isaac Manipulator uses a Transformer-based basic model and GPU acceleration library to accelerate path planning, ensuring that the robot can perform tasks more smoothly and efficiently. In addition, Isaac Manipulator can also be used to generate the grasping posture of the robotic arm.

Robotics powered by physical AI will change our industries and lives. Physical AI models can understand their surroundings and autonomously complete complex tasks in the physical world. Many complex tasks are difficult to program and rely on generative physical AI models trained using reinforcement learning in a simulation environment. With the NVIDIA Isaac Sim reference application based on NVIDIA Omniverse, developers can design, simulate, test, and train AI robots and autonomous machines in a virtual environment that obeys the laws of physics. NVIDIA Isaac Sim helps teams generate synthetic data, train robot policies, and build different application scenarios according to needs to verify the entire robot stack before deployment.

In this open class, Mr. Shu Jiaming first briefly introduced the important updates of the NVIDIA Isaac robot development platform, then explained how to use the Isaac Perceptor to improve the 3D surround vision perception capabilities of AMR, and then conducted an in-depth analysis of using the Isaac Manipulator to generate grasping postures and accelerate trajectory planning. Finally, Mr. Shu Jiaming shared how to test and evaluate in Isaac Sim.

Teacher Shu Jiaming's courseware PPT has been uploaded to this public account [Algorithm State】, you can reply to the keyword "Isaac" to obtain it.

Selected PPT

Partial QA

Q1: What specific extensions and improvements does Isaac Lab have based on Orbit?

A1:https://isaac-sim.github.io/IsaacLab/index.html

Q2: Is it easy to port the IsaacGymEnvs program to Isaac Sim?

A2：https://isaac-sim.github.io/IsaacLab/source/migration/migrating_from_isaacgymenvs.html

Q3: What are the main renderers integrated into Isaac Sim and what are their differences?

A3:https://docs.omniverse.nvidia.com/materials-and-rendering/latest/rtx-renderer.html#rtx-renderer

Full replay