Adaptive Computing in Robotics, Leveraging ROS 2 to Enable Software-Defined Hardware for FPGAs
This addresses the problem of scarce embedded expertise for roboticists by making adaptive computing more accessible, though it appears incremental as it builds on existing ROS 2 frameworks.
The paper tackles the challenge of enabling roboticists to use adaptive computing for software-defined hardware without requiring hardware expertise, by proposing a ROS 2-based architecture that integrates FPGAs as first-class participants, with core components released under an Apache 2.0 license.
Traditional software development in robotics is about programming functionality in the CPU of a given robot with a pre-defined architecture and constraints. With adaptive computing, instead, building a robotic behavior is about programming an architecture. By leveraging adaptive computing, roboticists can adapt one or more of the properties of its computing systems (e.g. its determinism, power consumption, security posture, or throughput) at run time. Roboticists are not, however, hardware engineers, and embedded expertise is scarce among them. This white paper adopts a ROS 2 roboticist-centric view for adaptive computing and proposes an architecture to include FPGAs as a first-class participant of the ROS 2 ecosystem. The architecture proposed is platform- and technology-agnostic, and is easily portable. The core components of the architecture are disclosed under an Apache 2.0 license, paving the way for roboticists to leverage adaptive computing and create software-defined hardware.