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Image Processing Helps Industrial Robots Process, Classify

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Automation technology developed at Southwest Research Institute (SwRI) enables industrial robots to visually classify and autonomously perform tasks. The technology can be applied to grinding, painting, polishing, cleaning, welding, sealing, and other industrial processes. According to the SwRI R&D team, the solution increases process repeatability and decreases the need for rework, while also reducing human exposure to dangerous environments.

The system uses machine learning algorithms developed at SwRI and classification software that work in conjunction with open-source tools such as Scan-N-PlanTM and ROS 2, the latest version of the open-source robot operation system. Traditional robot programming can be slow and tedious, requiring an expert in the loop with knowledge of computer-aided design.

A  robotic arm uses a 3D camera and machine vision software to scan and dynamically reconstruct contoured surfaces on aircraft parts. The robot uses 3D data to plan trajectories for surface preparation with sanders, grinders and other power tools. SwRI leveraged open-source Scan-N-PlanTM and ROS 2 software with custom algorithms, enabling intelligent image processing and classification with automated surface preparation. Courtesy of SwRI.
A  robotic arm uses a 3D camera and machine vision software to scan and dynamically reconstruct contoured surfaces on aircraft parts. The robot uses 3D data to plan trajectories for surface preparation with sanders, grinders, and other power tools. SwRI leveraged open-source Scan-N-PlanTM and ROS 2 software with custom algorithms, enabling intelligent image processing and classification with automated surface preparation. Courtesy of SwRI.
Scan-N-Plan, a ROS-Industrial technology, uses machine vision to scan parts, creating 3D mesh data that robots use to plan tool paths and process trajectories while performing real-time process monitoring. The solution includes custom machine vision algorithms that enable robots to apply various media with varying pressure based on the amount of surface work needed. Feature-based processing is also enabled through additions that use semantic segmentation approaches to apply the right tool to the right feature — cutting versus sanding, for example.

The solution also addresses the need to perform different tasks at different steps of a process, or during different processes altogether. The solution intelligently classifies regions and textures of part surfaces in various stages of work, Matt Robinson, a robotics R&D manager at SwRI, said.

“These are breakthroughs that will help prevent robots from over-sanding or over-grinding metal surfaces,” added Paul Evans, director of SwRI’s Manufacturing Technologies Department.

SwRI introduced the technology in June at the Automate 2022 trade show in Detroit.

Vision-Spectra.com
Jun 2022
GLOSSARY
machine vision
Interpretation of an image of an object or scene through the use of optical noncontact sensing mechanisms for the purpose of obtaining information and/or controlling machines or processes.
roboticrobotrobot armResearch & TechnologyeducationAutomate 2022Automatemachine learningmachine visionSwRIindustrialindustrial robotsimage processingalgorithmstextureimage classificationmachine vision softwaresurfaces

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