Giveaway has ended to win 1 AMD Xilinx Kria KR260 Robotics Starter Kit.


AMD Xilinx Kria KR260 Robotics Starter Kit Giveaway

In partnership with Avnet

Enter below for your chance to win an AMD Xilinx Kria KR260 Robotics Starter Kit

All About Circuits in collaboration with Avnet is giving away an AMD Xilinx Kria KR260 Robotics Starter Kit. The KR260 Robotics Starter Kit integrates high-performance industrial interfaces and features native ROS 2 support. It enables roboticists and industrial developers without FPGA expertise to develop hardware accelerated applications for robotics, machine vision, and industrial communication & control.

Key Features

Optimized for Kria K26 SOM

  • 2x 240-pin connectors
  • All SOM I/O available for sensor and network connectivity

High-Performance Industrial Vision

  • SLVS-EC Rx
  • 4x USB 3.0 for camera interfaces
  • DisplayPort 1.2a

Real-time Networking Interfaces

  • 4x RJ45 Ethernet Ports (10/100/1000)
  • 1 SFP+ optics (10G) for 10GE Vision

Expansion with PMODs and Rasberry Pi Headers

  • Extend to any sensor or interface
  • Broad Pmod ecosystem
  • e.g., Wi-Fi adapters, RS485

Giveaway already ended 542 days ago.

  • R
    ralphjy October 05, 2022

    I’ve used the Kria KV260 and it’s been great to prototype Vision AI.  Looking forward to trying a KR260 to build an AI Robot.  I’ve been experimenting with a few mobile chassis that I could use with it.

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  • Raju Machupalli October 07, 2022

    I worked on robotic arm for chess using RFID label on pawns and readers at the board bottom. Now I wanna try that using vision based instead of RFIDs. KR260 can be very handy for the project.

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  • V
    vadergsg9 October 15, 2022

    I am starting a project to get masters degree, my idea is an automation system for urban farms, using edge computing, AI and cloud computing for certain microservices.  The SFP module is a plus that I was looking for to bring 10Gb speed to the place where I would only have a mobile phone signal on 4G networks, which is not a good idea to send the amount of images to be analyzed in the cloud.  Local sensor analyzes and algorithms will be worked out at the FPGA on site.

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