New-Tech Europe Magazine | Q2 2022

Making Robots More Efficient with Adaptive Computing

Víctor Mayoral-Vilches, Robotics System Architect, Adaptive & Embedded Computing Group, AMD

As roboticists encounter limitations imposed by traditional processor architectures, customization and paral lelism are needed to meet forthcoming performance, security, and safety challenges Software developers targeting robotics applications face a growing struggle to meet performance requirements, ensure real-time determinism, and ensure adequate safety and security. Increasingly, the general-purpose nature of the scalar (CPU) processor architectures at the heart of the machine, together with limitations on performance scaling, presents a barrier to meeting the diverse requirements placed on today’s industrial robots. Common problems include time inefficiencies that impact determinism, excessive power consumption, and security issues. A further challenge to security is that the hardware cannot be reconfigured to update protection against evolving cyber-threats.

A new generation of computing platforms, better suited to the demands of robot ics, is now emerging. These modules comprise heterogeneous processing elements that allow roboticists to build flexible compute architectures. This article assesses their make-up by examining the various compute resources that are available to roboticists, including CPUs, DSPs, GPUs, FPGAs, and ASICs. Each has specific strengths and therefore a continued role as the evolution of robotics technology progresses. Compute Technologies for Robotics Applications Scalar Processors (CPUs) CPUs, as scalar processing elements, can handle complex algorithms with diverse decision trees and a broad set of libraries in an efficient manner. Although CPUs are highly flexible,

and multi-core processors can handle different tasks running simultaneously without distractions or coordination problems, their underlying hardware is fixed. Most CPUs still operate on the stored-program computer principle, where data is brought to the processor from memory, operated on, and then written back to memory. The focal point of the architecture is the arithmetic logic unit (ALU), which requires data to be moved in and out for every operation. Fundamentally, each CPU operates in a sequential fashion, one instruction at a time, and many steps are typically needed to complete a task. Despite these drawbacks, scalar CPUs have a fundamental role in modern robot architectures. They are well suited to coordinating information flows across the various subsystems and components for sensing, actuation, and cognition.

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