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.
Innovations in Automation Blog
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 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.