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  • NVIDIA Isaac SDK

    Build and deploy commercial-grade, AI-powered robots. The NVIDIA Isaac SDK? is a toolkit that includes building blocks and tools that accelerate robot developments that require the increased perception and navigation features enabled by AI.

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    NVIDIA Isaac SDK for Autonomous Mobile Robots (AMRs)

    Artificial Intelligence

    The SDK features GPU-accelerated algorithms and deep neural networks (DNNs) for perception and planning, and machine learning workflows for supervised and reinforcement learning.


    Modular robotic algorithms provide sensing, planning, or actuation for both navigation use cases.


    Training and continuous testing in high- fidelity physics and photorealistic simulation accelerates robot development and deployment.

    Rich Software Platform for AI-based Robot Development

    The SDK includes the Isaac Engine (an application framework), Isaac GEMS (packages with high-performance robotics algorithms), Isaac Apps (reference applications) and NVIDIA Isaac Sim? (a powerful simulation platform). These tools and APIs accelerate robot development by making it easier to add for perception and navigation.

    Isaac SDK platform

    Delivering GPU-Accelerated Real-Time Performance Using Isaac SDK

    DNN-Based GEMS Performance

    Inference Resolution Jetson Xavier? NX Frames per Second Jetson AGX Xavier? Frames per Second
    13D pose: Pose convolutional neural network (CNN)
    + DetectNetv2,ResNet-18
    640x368 47 82
    Object Detection (Detect_netv2, resnet18) 640x368 120 205
    Freespace Segmentation (Unet) 512x256 49 86
    All measurements done with MAX perf mode and MAX Clocks. 13D pose for object detection used default unpruned models. All DNNs use FP16.

    Non-DNN GEMS Performance

    Resolution Jetson Xavier? NX Execution Time Jetson AGX Xavier? Execution Time
    Superpixel 640 x 360 20.72 ms 16.89 ms
    AprilTag detection 701 x 935 17.51 ms 11.64 ms
    2Two-lidar initial/startup global localization 1250 x 500 (binary map) 6.93 s 4.57 s
    3Evidential grid maps (EGM) fusion 256 x 256 (local map) 8.94 ms 3.33 ms
    All measurements done with MAX perf mode and MAX Clocks. 22-lidar localization unit measurement is "initial localization complete" (or everytime localization is lost). 3EGM measurement unit is “single fusion operation” for local map 256X256X3 (mass values).

    Featured GPU-Accelerated GEMS

    GEMS are high-performance robotics algorithms.

    3D Object Pose Estimation

    An updated 3D pose estimation pipeline consisting of object detection followed by 3D pose estimation, and then followed by pose refinement using depth image.

    More Info

    Multi-Lidar Localization

    The updated lidar based localization algorithm now supports an arbitrary number of lidars to improve performance and support larger maps.

    Evidential Grid Maps

    EGM-based local mapping provides clean and fast fusion output. All Isaac SDK navigation applications leverage EGM.

    More Info

    See More Isaac SDK GEMS below

    Visual SLAM based Localization

    Isaac’s VSLAM localization (preview release) offers best in class vision-based localization performance. In fact, it is a top performer when looking at real-time stereo VSLAM implementations based on publicly available results using the KITTI database. Developers interested in exploring the benefits of Visual based localization can get started in Isaac Sim or on the NVIDIA Carter robot.

    Learn more about the Isaac Visual SLAM Localization

    Isaac Remote Control (RC)

    Isaac Remote Control (preview release) provides low-latency, video-streaming for control applications to the remote robot operator. Based on Cloud XR, Isaac RC is a highly performant software stack that offers differentiated Quality-Of-Service (QOS).

    Learn more about Isaac RC for teleoperations

    Indoor Mobile Robot, Carter v2.0

    Carter v2.0 is the indoor mobile robot reference design platform for Isaac SDK users. It is based on Segway Robotics’ RMPLite 220 Drivetrain with integrated IMU and is very flexible allowing for additional sensors to be added and evaluated.

    Access detailed information about assembling Carter v2.0

    Isaac Sim, Robotics Simulator

    Isaac Sim, Robotics Simulator

    Testing and training in simulation can save time and effort. Isaac Sim provides a photo-realistic, physics accurate simulation environment that runs seamlessly with Isaac SDK. Many features in the SDK are already supported in Isaac Sim including Carter 2.0, Isaac RC, and VSLAM-based localization.

    Learn More about Isaac Sim Applications in Isaac SDK

    Isaac SDK Partners

    Isaac SDK partners offer drivers that seamlessly integrate with the Isaac SDK. A complete list of drivers and Isaac compatible hardware can be found here. A complete view of NVIDIA’s autonomous machines ecosystem can be found here.

    Sick Sensor Intelligence
    Universal Robots
    e-con Systems


    “BMW Group is committed to the Power of Choice for our customers—customization of diverse features across diverse vehicles for diverse customers. Manufacturing high-quality, highly customized cars, on multiple models, with higher volume, on one factory line, requires advanced computing solutions from end to end. Our collaboration with NVIDIA allows us to develop the future-of-factory logistics today and to ultimately delight BMW Group customers worldwide.”

    — BMW Group

    “The Government Technology Agency of Singapore developed add-on capabilities for Boston Dynamics’ ‘Spot’ legged robot that enabled us to deploy it to support safe distancing operations in a public park in Singapore. Our project included AI-based algorithms such as Visual SLAM running on the NVIDIA Jetson platform to increase the robot’s autonomy and its ability to adapt to new environments; we also leveraged the NVIDIA Isaac SDK for autonomous navigation of the ‘Spot’ robot.”

    — Government Technology Agency of Singapore


    Detailed View of Isaac Platform

    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.

    Computational Graph Computational Graph

    Compute Graph & Entity Component Architecture

    • Helps break down a complex robotics use case into smaller building blocks and customizes it by configuring pre-packaged components
    • Avoids host-device memory copies and increases application performance by attaching CUDA? buffer objects to messages
    • Groups nodes into subgraphs, effectively combining them into a robotics application

    Tools for visualization, record, replay and more

    • Comes with a customizable visualization framework for creating visualizations of variable plots, drawings, camera image overlays, or 3D scenes
    • Comes with Isaac WebSight for inspecting and debugging robotics applications in a web browser
    "Isaac WebSight" application

    Python API

    • Makes it possible to writes fully functional Isaac codelets in Python
    • Leverages Isaac C++ and high-performance GEMS in Python applications
    • Provides easy management of Isaac applications from a Jupyter Notebook

    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 for their robot.

    Deep Object Pose Estimation (DOPE)

    Deep object pose estimation (DOPE) provides a novel model to estimate the six degrees of freedom (6DOF) pose of an object using an RGB image. It’s suitable for manipulation tasks.

    More Info

    NVIDIA EGX? Robot Mission Submission

    An application that allows users to submit missions to a robot and control multiple robots via programmable mission dependencies

    More Info

    Localization Monitoring

    An algorithm that monitors and validates lidar communications to help recover from repeated robot mislocalization

    More Info

    Visual SLAM based Localization

    Vision-based localization GEM

    More Info

    LQR Planner with Trajectory Validation

    A planning algorithm that avoids obstacles by checking trajectories for collisions, range, and speed before execution

    Global Planner with Semantic Zones

    A customizable global planning algorithm that leverages semantics zone information like reduced speed, restricted access, or unidirectional movement

    OTG5 Straight Motion Planner

    An algorithm that provides for smooth, predictable, and straight forward and backward movement

    More Info

    Customizable Planner Cost Functions

    A flexible interface for LQR planner cost functions, which can be customized, combined and used on different robots

    Customizable Planner Cost Functions
    Depth Camera Sensor Certification

    A well defined process to help Jetson depth camera partners bring up their cameras on the Isaac SDK

    Factory of the Future (FoF) / Intralogistics Production Application

    An application that demonstrates the breadth of the Isaac SDK’s navigation and manipulation capabilities, showing how robots work together to complete a mission in a simulated factory environment.

    More Info

    Industrial Pick-and-Place Python Application

    An application that shows our Isaac SDK pick-and-place manipulation capabilities using the UR10 robot arm.

    More Info

    Cube Stacking Pick-and-Place Python Application

    An application that shows our Isaac SDK pick-and-place manipulation capabilities using the Franka robot arm

    More Info

    3D Pose Estimation Docker Container

    An NGC? docker that makes it easy to experiment in simulation (Unity 3D) with the Isaac Pose CNN GEM

    More Info

    Jetbot Application

    Follows a ball in simulation to demonstrate how to do training and inference in simulation for a low-cost robot

    More Info

    Object Detection/Pose Estimation Evaluation

    A pipeline for simulation data that allows users to evaluate performance of objection and 3D pose estimation models

    More Info

    Isaac Sim provides the essential features for building virtual robotic worlds and experiments. Isaac Sim supports navigation and manipulation applications through the Isaac SDK with RGB-D, lidar and inertial measurement unit (IMU) sensors, domain randomization, ground truth labeling, segmentation, and bounding boxes.

    Machine Learning Training in Simulation (Pose Estimation)

    Training of pose estimation pipeline using machine learning workflows possible with Isaac SDK

    Domain Randomization

    Shows random changes in material (texture, color), light direction, light conditions, sunlight changes, placement of objects/obstacles, floors, etc., to train robot perception and behavior as well as test for robust behavior in real life

    Multi Robot Simulation with Hardware in-the Loop (HIL)

    Multiple Carter robots operating simultaneously in a virtual warehouse. Each operated by an independent Jetson Xavier

    More information on Isaac Sim ?

    Build and deploy commercial-grade, AI-powered robots using the Isaac SDK.

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