UP Squared RoboMaker Pro Kit
The new UP Squared RoboMaker Pro Kit, powered by Intel®, Amazon Web Services and Cogniteam, provides an easy approach to create a machine vision application for an autonomous mobile robot (AMR) in a single day.
With Intel® Movidius™ Myriad™ X vision technology, deep learning capabilities at the edge and pre-configured ROS tools from AWS RoboMaker, robots can perform more intelligent tasks, such as enabling avoidance of dynamic obstacles within one second & replanning the path.
This seamless integration of embedded system and AWS RoboMaker delivers an unprecedented experience of AI simulation-to-reality while allowing developers to speed up the time to production.
Powerful vision. Powered by Intel®
With Intel® x7-E3950 processor, UP Squared is designed with low-power high-performance components, UP Squared is a favorite among developers of mobile applications.
Featuring Intel® Movidius™ Myriad™ X, it is capable of speeds up to 105 fps (80 typical). This outperforming VPU is dedicated hardware-based acceleration for deep neural networks for powering AI edge computing processes.
Developers can take a shortcut by using off-the-shelf tech, building an AMR in one day.
AWS RoboMaker is pre-integrated with popular AWS analytics, machine learning, and monitoring services. It’s very easy to add functions like video streaming, face and object recognition, voice command and response, or metrics and logs collection to your robotics application.
AWS RoboMaker services are exposed as ROS packages so that developers can easily use them to build intelligent functions into their robotics applications without having to learn a new framework or programming language.
Vision from edge to cloud
Intel® RealSense™ depth camera D435i with an inertial measurement unit (IMU) inside, which opens the door for rudimentary SLAM and tracking applications allowing better point-cloud alignment. Additionally, IMU allows your application to refine its depth awareness in any situation where the camera moves.
OpenVINO™ (Open visual inference and neural network optimization) toolkit provides a ROS–adapted runtime framework of neural network. By leveraging Intel® OpenVINO™ toolkit and corresponding libraries, it can reinforce the efficiency of deploying applications for vision inference.
What can you achieve with this kit?
Enable your AMR to see in 3D and make autonomous decisions.Utilizing the 4 Key components in AWS RoboMaker and executing SLAM efficiently
- Integrated Development Environment: All dependencies are pre-packed and ready to go, so developers can easily spin up a ROS environment.
- Simulation: Accelerate testing of your ROS applications with a simple API call, developers can spin up their ROS applications into a simulation environment, and access ROS simulation tools such as Gazebo, rqt, rviz (to view the robot’s SLAM), Terminal.
- Fleet Management: Deploy your robot applications to robots in production over-the-air and it leverages AWS Greengrass daemon that would run on your robots.
- Cloud Extensions for ROS: Enable developers to extend their ROS applications into the cloud and leverage cloud services from AWS, i.e. Boto3 and ECS SDK. Other cloud extensions automatically create connections and make API calls to AWS services, such as Amazon Kinesis, Amazon Rekognition, Amazon Lex, and more.
This enables us to free our CPU for decision making while processing data and building the world model of the robot in an optimized manner, by having production ready boards integrated with Intel® Movidius™ Myriad™ X VPU and a depth camera enables to jump from low-level control of the robot to a fully autonomous robot with cloud connectivity within days. ❞
See its possibilities
By leveraging UP Squared RoboMaker Pro Kit, developers can easily upgrade their PoC and scale to production.
- UP Squared board with Intel® Atom® X7-E3950 processor, onboard 4GB DDR4, 64GB eMMC
- Intel® RealSense™ depth camera D435i (IMU inside)
- UP AI Core X – Mini-PCIe card with the Intel® Movidius™ Myriad™ X
- Intel® AC9260 WiFi Kit (via M.2 2230)
- Servo and DC motor with encoder
- Cogniteam Motor Control Board
- Ubuntu* 18.04 desktop
- ROS1 – melodic/ROS2 – dashing
- Intel® Distribution of OpenVINO™ toolkit 2019 R1.1 release
- Intel® Media SDK
- Drivers for Intel® VTune™ Amplifier, Intel® Energy Profiler, Intel® Graphics Performance Analyzers
|UP Squared RoboMaker Pro Kit|
|Hardware - UP Squared|
|CPU||Intel Atom® x7-E3950 (up to 2.00 GHz)|
|Graphics||Intel® HD Graphics 505, supporting 4K Codec Decode and Encode for HEVC4, H.264, VP8|
|RAM||4GB (dual channel) LPDDR4|
|AI Accelerator||UP AI Core X with 1x Intel® Movidius™ Myriad™ X VPU 2485 (via Mini-PCIe)|
|Storage capacity||64GB eMMC|
|OS||Pre-load Ubuntu image|
|Ethernet||2x Gb Ethernet (full speed) RJ-45|
|WiFi & Bluetooth||Intel® AC9260 card (via M.2 2230)|
|Display interface||1x eDP|
|Camera Interface||1x MIPI-CSI (2 lane) &
1x MIPI-CSI (4 lane)
|USB||2x USB 2.0 pin header
1x USB3.0 OTG
3x USB3.0 (Type A)
|Expansion||1x 40 pin GP-bus enabled by Altera MAX 10 FPGA
1x 60 pin EXHAT
1x Mini-PCIe (used by AI Accelerator)
1x M.2 2230 E-key (used by WiFi & Bluetooth)
|Dimension||85.6 mm × 90 mm (3.37" x 3.54")|
|Power input||5V@6A with DC jack 5.5/2.1mm|
|Certificate||CE/FCC Class A, RoHS compliant, REACH, Microsoft Azure certified|
|Hardware - Intel® RealSense™ depth camera D435i|
|Depth Field of View (FOV)||87°±3° x 58°±1° x 95°±3°|
|Depth Output Resolution & Frame Rate||Up to 1280 x 720 active stereo depth resolution.
Up to 90 fps.
|Image Sensor Technology||Global Shutter, 3μm x 3μm pixel size|
|Minimum Depth Distance (Min-Z)||0.11 m|
|Inertial Measurement Unit (IMU)||Yes|
|Click here to see more information about RealSense™ camera D435i|
|Battery (not included in the kit)|
(not included in the kit)
|Lipo battery with T connector 7.4V 2 cell|
(not included in the kit)
|Charger 2S-3S 7.4-11.1 V for Lipo Battery|
|Software - Cogniteam|
|Get started||Connecting all parts within the kit|
|UP Squared RoboMaker Pro Kit supports ROS & ROS2|
|Platforms||Tested on Ubuntu|
Maintained on other Linux flavors as well as OS X
|ROS2 is currently being CI tested and supported on Ubuntu Xenial, OS X El Capitan as well as Windows 10|
|C++||C++03 // don’t use C++11 features in its API||Mainly uses C++11
Start and plan to use C++14 & C++17
|Python||Target Python 2||>= Python 3.5|
|Middleware||Custom serialization format (transport protocol + central discovery mechanism)||Currently, all implementations of this interface are based on the DDS standard.|
|Unify duration and time types||The duration and time types are defined in the client libraries, they are in C++ and Python||In ROS2 these types are defined as messages and therefore are consistent across languages.|
|Components with life cycle||In ROS every node usually has its own main function.||The life cycle can be used by tools like roslaunch to start a system composed of many components in a deterministic way.|
|Threading model||In ROS the developer can only choose between single-threaded execution or multi-threaded execution.||In ROS2 more granular execution models are available and custom executors can be implemented easily.|
|Multiple nodes||In ROS it is not possible to create more than one node in a process.||In ROS2 it is possible to create multiple nodes in a process.|
|roslaunch||In ROS roslaunch files are defined in XML with very limited capabilities.||In ROS2 launch files are written in Python which enables to use more complex logic like conditionals etc.|
|AWS Robomaker||Cross-Compiling Applications with Colcon
Capturing log data with rosout