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.
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.
Whether you are adding another piece of automation to your factory floor or debating whether bringing automation into your operation is right for your business, there is a lot to consider. From new equipment to reorganizing floor space for the new set-up, you will have a laundry list of tasks to complete before your newly automated system is ready to use. One of the most important items on that list will be safety. How do you ensure this system is safe for those working around it? What additional items should be on the shopping list to aid in safety? What do you base your safety decisions around?
Industrial robotics continue to rise in levels of autonomy, intelligence and complexity, which enables them to fill more roles within the manufacturing process. However, as those systems rise in their independence, the need to ensure they are secure against cyberattacks has risen accordingly. Identifying the risks to robotics systems and corresponding solutions will help prevent costly cyberattacks to industrial control systems in the future.
One of the biggest drivers for automation is keeping humans out of dangerous situations. While significant effort has been invested in automating dangerous tasks in open environments, similar focus has not been placed on applying automation technologies to confined spaces. A major obstacle to this has been developing systems that can move in a physically constrained environment yet also have the stability to carry out high-force processes such as drilling, sanding, contact sensing and media blasting
Inkjet printing methods on 2D surfaces have been a mature technology for many years within the high-resolution printing domain. Today, this technology is being expanded to 3D surfaces via robotic systems. At Southwest Research Institute, a large-scale prototype with industrial inkjet printing heads mounted to a robotic manipulator was developed, enabling digital graphic printing on 3D surfaces. Initially created for the aerospace industry, this inkjet prototype system was developed to apply colored graphics, also known as liveries, to the exterior of commercial aircraft. Since being demonstrated in 2019, SwRI has developed inkjet systems for other markets including automotive and logistics—printing both multi-colored graphics and non-graphical, functional fluids.
Methane emissions are a critical topic of interest as government and industry address rapid warming of the global climate. Methane, a potent greenhouse gas, traps heat in the atmosphere at a much higher rate than carbon dioxide (CO2). Methane also makes up a significant percentage of fugitive emissions from oil and gas infrastructure that scientists have been trying to detect for many years.
The no-code development movement describes the proliferation of tools and frameworks that enable people untrained in traditional coding languages to develop useful software.
This is fourth and final article in our series on collaborative robots. In previous posts we examined the benefits and limitations of cobots. Assuming you’ve decided that a cobot is indeed the right decision for your application, read on. In this post we will look at how to pick the right cobot from the many options on the market.