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Industrial Robotics & Automation

Industrial Robotics & Automation


For more than 35 years, SwRI has been developing innovative automation and robotics solutions. World-class experts and experienced engineers comprise the automation engineering staff. Automation engineering facilities include state-of-the-art laboratories and large prototype areas for development.

Innovations in Automation Blog

Transitioning Spacecraft to FPGA Computing for Faster Machine Learning Object Detection

Digitized outline of the brain divided into four sections depicting car networks, AI, security and robotics with the words Intelligent Systems Insights

Computing in space tends to be constrained by the size, weight, power and cost of radiation-hardened systems that can fit on spacecraft. Historically, these constraints have ruled out deployment of machine learning (ML) and artificial intelligence (AI) applications, which require substantial memory and power to automate image detection and other tasks.

Machine Vision Enables Advanced Automation

Humans can see damage to a propeller blade under normal light and feel damaged areas with touch.

Many manufacturing processes operate using fixed or hard automation equipment that perform production tasks with limited sensory inputs. For more complex applications, simple cameras or sensors can detect an object’s presence, position, size, or thickness. Machine vision solutions can be applied when objects are more complex, less constrained, or their appearance needs to be evaluated. This blog post will review three applications to provide insights into machine vision’s role in advanced automation.

The ROS 1 vs ROS 2 Transition

Illustration of how various parts in a manufacturing system can be orchestrated to automate tasks

The Robot Operating System (ROS) was first released by Open Robotics in 2007 with the intent to provide open-source software frameworks, tools and libraries for robot development. A typical ROS system is comprised of independent nodes that can communicate with each other through publisher/subscriber relationships. A key part that makes ROS so useful in robotic development is that these nodes do not need to be on the same system or even used by the same architecture. This flexibility makes ROS easily adaptable to the needs of the user.