Industry’s first Robotic AI Development Platform with Simulation, Navigation and Manipulation.

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Artificial Intelligence

GPU-accelerated algorithms and DNNs for perception & planning; ML workflows for training and transfer learning

Perception and Navigation

Modular robotic algorithms that provide sensing, planning, or actuation

Simulation

Accelerated robot development/deployment using training/testing in simulation




The SDK includes the Isaac Engine (application framework), Isaac GEMs (packages with high-performance robotics algorithms), Isaac Apps (reference applications) and Isaac Sim for Navigation (a powerful simulation platform). These tools and APIs accelerate robot development by making it easier to add artificial intelligence (AI) for perception and navigation into robots.




Isaac SDK runs on and is optimized for NVIDIA® Jetson AGX Xavier™ systems. Jetson AGX systems provide the performance and power efficiency to run autonomous machines software, faster and with less power. The Jetson platform is supported by the JetPack SDK, which includes NVIDIA CUDA®, DeepStream SDK, libraries for deep learning, computer vision, accelerated computing, and multimedia. The platform supports drivers for a wide range of sensors.

Isaac SDK uses machine learning and continuous testing workflows with Isaac Sim running on NVIDIA® DGX™ Systems. Developed to meet the demands of AI and analytics, NVIDIA® DGX™ Systems are built on the revolutionary NVIDIA Volta™ GPU platform. Combined with innovative GPU-optimized software and simplified management tools, these fully-integrated solutions are designed to give data scientists the most powerful tools for AI and ML.



The Isaac Engine is a software framework to easily build modular robotics applications. It enables high-performance data processing and deep learning for intelligent robots. Robotics applications developed on Isaac Robot Engine can seamlessly run on edge devices like the NVIDIA® Jetson AGX Xavier™ and NVIDIA® Jetson Nano™, as well as on a workstation with a discrete NVIDIA® GPU like T4.


Entity-Component Architecture

  • Break down complex robotics use case into smaller building blocks
  • Customize features by configuring pre-packaged components
  • Add new features by developing custom components
  • Simplify and customize robotics applications using pre-packaged components
  • Avoid host-device memory copies, increase application performance by attaching CUDA buffer objects to messages
  • Group nodes into subgraphs, effectively combine them into a robotics application

Computational Graph

Computational Graph

  • Applications consist of multiple nodes and use inter-node communication to exchange data between them
  • Avoid host-device memory copies and increase the performance of your application by attaching CUDA buffer objects to messages
  • Group nodes into subgraphs and effectively combine them into a robotics application




Visualization

  • The Isaac Robot Engine also comes with a customizable visualization framework to create visualizations for variable plots, drawings, camera image overlays, or 3D scenes.
  • Developers can use Isaac WebSight to inspect and debug their robotics applications in a web browser
"Isaac WebSight" application



Distributed Workspace

Advanced Build System

  • Isaac SDK uses Bazel for tracking dependencies, building source code, testing, and packaging of robotics applications
  • Automatically pull external dependencies such as OpenCV, ROS or other robotics open-source libraries
  • Partners can create their workspaces to add support for new hardware or algorithms to Isaac SDK

C API

  • Allows the use of Isaac SDK features without fully integrating software stack with ISAAC SDK
  • Don’t have to use Bazel for code base or write Isaac codelets
  • Communicate with Isaac apps from languages other than C++


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GEMs are modular capabilities for sensing, planning, or actuation that can be easily plugged into a robotics application. For example, developers can add obstacle detection, stereo depth estimation, or human speech recognition to enrich their robot use cases. Similarly, developers can use the Isaac navigation stack, a collection of modules to build a robotics navigation application, to their robot. The GEMs can be used outside Isaac SDK using C API without fully integrating a software stack with ISAAC SDK.

In addition to the GEMs described below, Isaac SDK packs GEMS for Audio (text to speech, speech recognition), Fiducials, Superpixels, Path planning, etc.



Multi Class Segmentation DNN

Deep Neural Network (DNN) segmentation of images into classes of interest like drivable space and obstacles.


This video shows a DNN performing the segmentation of multiple classes including collision free space.


Object Detection (ResNet)

Object detection using ResNet backbone feature extractor. NVIDIA Transfer Learning Toolkit (TLT) is used to train/fine-tune/prune models.


This video shows the result of object detection from a DNN trained using NVIDIA transfer learning toolkit (TLT)


Stereo Visual Inertial Odometry

Track 3D pose of the camera by analyzing stereo image video stream and IMU.

This video shows that the fusion of IMU and visual odometry. VIO is stable even if image is blurred

3D Object Pose Estimation

Detection of objects with 3D CAD models & estimation of 3D pose using an autoencoder model.

This video shows the detection & pose estimation of a dolly


2D Skeleton Pose Estimation DNN

Real-time detection of human pose using OpenPose DNN as a backbone.

This video shows sensor fusion from RGB + Depth + Pose Sensor. 3D skeleton visualization in bottom right; 2D skeleton reprojection to 3D from the depth camera.
DeepStream for Robotics

Integration of DeepStream streaming analytics toolkit for AI-based video/image perception.








Robot Platforms/Motors
  • Differential Wheelbase (Segway RMP210)
  • Servo Motors (Dynamixel)




Sensors
  • Stereo Camera (Zed)
  • Structured Light Depth Camera (RealSense)
  • Lidar (Velodyne VLP16)
  • IMU (Bosch Sensortec BMI160)


More
  • Stereo Depth DNN
  • Super Pixel
  • AprilTags
  • ORB Feature Tracker
  • Image Warping
  • ...


Get Started with Isaac SDK



Carter the delivery robot

Carter is an Isaac SDK reference robot platform for autonomous indoor delivery and logistics based on the NVIDIA Jetson platform. Developers can build their own Carter robot using sample applications. With the NVIDIA Isaac SDK, developers can add capabilities for localization, autonomous navigation, map edition, path planning, and state machines. Some of the included apps are Map Creation, Map Waypoint, Pose, Patrol, Random, etc.


Documentation



Kaya the robot to get started with robotics

People who would like to get started with Isaac SDK can build their own small robot platform using the Kaya reference robot platform. Kaya can be built using off-the-shelf components and 3D printed parts. The low-cost Kaya robot takes advantage of the new NVIDIA® Jetson Nano™. Samples applications built for the platform include April tag detection, obstacle avoidance, remote operation, object classification based on Yolo and much more. Some of the included apps are Follow-me, Mapping, Detect/Classify, etc.


Documentation




Isaac Sim is a virtual robotics laboratory and a high-fidelity 3D world simulator that accelerates research, design, and development by reducing cost and risk.

Isaac Sim includes features like Domain Randomization (scene parameter control) and Scenario Management (rapidly testing robot in different scenarios). Robots can be simulated with virtual sensors (RGB, stereo, depth, LIDAR, IMU). Robots in Isaac Sim are tightly coupled to the tools and frameworks in Isaac SDK, enabling easy transfer of algorithms and data between physical and virtual robots.


Multi Robot Simulation
This video shows multiple Carter robots operating simultaneously in a virtual warehouse. Each Carter robot is operated by an independent Jetson AGX Xavier computer (Hardware in the loop).
ML Training in Simulation



This video shows simulated samples of a dolly (with actual CAD model) that are used to train the object detection and pose estimation neural networks.

This video shows procedurally generated simulated images used for segmentation network training



Get Started with Isaac Sim for Navigation     Learn more about Isaac Sim