Edge Insights for Autonomous Mobile Robots
Edge Insights for Autonomous Mobile Robots (EI for AMR) offers
containerized software packages and pre-validated hardware modules for
sensor data ingestion, classification, environment modelling, action
planning, action control. Based on the Robot Operating System 2 (ROS* 2),
it also includes the OpenVINO™ toolkit, Intel® oneAPI Base Toolkit (Base Kit), Intel® RealSense™ SDK,
and other software dependencies in a container, along with the source code, as
well as reference algorithms and deep learning models as working examples.
The currently supported versions are:
- Base OS: Ubuntu* 20.04 LTS
- ROS 2 with data distribution service: Foxy
- OpenVINO™: 2021.4
- Intel® oneAPI Base Toolkit: 2021.4
- Intel® RealSense™ SDK: v2.50
- Simulation: Gazebo* v11.8.1 + Agile Robotics for Industrial Automation Competition (ARIAC) world
In addition to autonomous mobility, this package showcases map building
and Simultaneous Localization And Mapping (SLAM) loop closure
functionality. The package uses an open source version of visual SLAM
with camera input from an Intel® RealSense™ camera. Optionally, the
package allows you to run Light Detection and Ranging (LIDAR) based SLAM
and compare those results with visual SLAM results on accuracy and
performance indicators. In addition, this package detects the objects
and highlights them in the map. Depending on the platform that is used,
AI workloads are run on an integrated GPU or on Intel® Movidius™ Myriad™
X accelerator.
Edge Insights for Autonomous Mobile Robots helps to address various
industrial and manufacturing uses, consumer market and smart cities use
cases, which include data collection, storage, and analytics on a
variety of hardware nodes across the factory floor. See How it Works.
Use the Get Started Guide
for installation instructions and an introduction to the Edge Software
command line interface to learn how to manage Intel® Developer Catalog
packages.
When set up is complete, see Edge Insights for Autonomous Mobile Robots Tutorials
for step-by-step, hands-on walkthroughs, including how to run a demo
ROS 2 sample application inside the EI for AMR Docker* container.