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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, navigation, and manipulation features enabled by AI.

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Isaac SDK-Powered Robots Collaborating
in Simulated Factory Environment




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.

Navigation and Manipulation

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

Simulation

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.



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 llidars 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



Featured Use Case—AI-Based Intralogistics

Factories, warehouses, and distribution centers are very dynamic environments. The robots that move products and parts in constantly changing environments must be flexible and adaptable. Isaac SDK provides key AI-based perception, localization, and manipulation planning GEMS allowing robot developers to build the robots for tomorrow's intralogistics challenge.

See BMW Presentation on Intralogistics with Isaac


Simulation Based Robot Development

Developing, testing, and deploying robots is a slow and costly process. Leveraging a simulation approach can greatly reduce the time and expense of developing a new robot. Isaac Sim, which is built on top of the NVIDIA Omniverse platform, leverages GPU technology to deliver realistic physics and compelling photorealism in simulation. Additionally, Isaac Sim easily connects the robot’s brains to the simulated world.

See BMW presentation on Simulation-First Approach for Development


Add AI to Existing Robot Platforms

Many robot makers have significant investments in their robot software stacks. But they face the challenge of upgrading the robot with new features that have recently been enabled by advances in AI technologies. The ROS BRIDGE capabilities supported in Isaac SDK release 2020.2 allow developers to add GPU-accelerated GEMS like 3D pose estimation to their ROS based systems.

Read Blog about how to use Isaac and ROS together




Isaac SDK Partners

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





Testimonials

“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

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.



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.

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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


Simulation Stereo Visual Inertial Odometry

An application that allows users to visualize a 3D map of an environment with point clouds built online

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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

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Customizable Planner Cost Functions

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

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.

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Industrial Pick-and-Place Python Application

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

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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

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Jetbot Application

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

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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.

Get Started