Summary
Building a robot requires one to carefully select components that exchange information across networks while meeting timing deadlines.
In a way, a robot is a network of networks.
One that comprises sensors to perceive the world, actuators to produce a physical change, and dedicated computational resources to process it all and respond coherently, in real-time, according to its application, and in a secure manner.
Building a robot is thereby very close to an art, the art of system integration.
This talk introduces the Kria Robotics Stack (KRS), a complete integrated set of utilities to accelerate the development and maintenance of industrial-grade robotic solutions using Xilinx's Kria™ Adaptive SOMs portfolio, bridging between the world of roboticists and the world of Xilinx.
KRS hardware accelerates Robot Operating System (ROS), the de facto standard in robotics.
Most roboticists these days use ROS to create robots, from Autonomous Mobile Robots (AMRs) to industrial robotic arms, going all the way to automotive.
ROS is the present and the future of robotics.
Víctor will describe how adaptive computing can be integrated in ROS 2 and how Xilinx is contributing to the ROS community driving the hardware acceleration efforts at the Hardware Acceleration Working Group (HAWG).
Through practical examples, Víctor will analyze some of the main bottlenecks that roboticists encounter while building their computational graphs and introduce how his team's work is helping leverage hardware acceleration in ROS 2 packages seamlessly in combination with HLS.
The result is that accelerating (or offloading to the FPGA) ROS nodes becomes as easy as re-compiling ROS workspaces, no hardware expertise needed.
Víctor will also present results and benchmarks of the impact of acceleration in ROS 2.
He'll also show comparisons across different edge devices and reproducible results that show evidence on why Xilinx's adaptive SOMs are the best edge compute substrate to build secure, reconfigurable, and adaptive robots with ROS 2.
