In a solution for shiny objects demonstrated by SwRI at ‘ 2019’ which took place on April 8-11th, 2019, at McCormick Place in Chicago. The Southwest research institute (SwRI) and ROI-industrial developed a solution that enables to scan and manipulate metallic objects that are too ‘shiny’ for to process. The industry consortium initiated by SwRI in 2012 to support cost-shared applied R&D for advanced factory . The project includes intelligent part reconstruction using the second generation of the Operating System (ROS2) framework to improve 3D perception when autonomously sand and finish parts.
Due to the ‘visual noise’ that scatters off highly reflective surfaces, cameras and algorithms have historically struggled to render accurate 3D images of metallic objects. This challenge limits of and surface finishing processes in aerospace and automotive manufacturing.
SwRI and ROI-industrial integrated part reconstruction within the ROS2 framework to improve industrial robotics 3D image perception for path planning with way-point full operations such as parts sanding. With the help of the Southwest Research institute (SwRI) in partnership with ROI-industrial, joined truncated sign distance field algorithms stitch together several images, or point clouds, at a higher rate. The solution uses trajectory optimization or TrajOpt for motion planning, within the ROS-industrial Scan-N-plan framework, to enable real-time trajectory planning from 3D scan data. The and can be changed out with relatively little effort, said Matt Robinson, the SwRI manager who supports ROI-industrial.
According to Matt Robinson, it is a great case study meant for the benefits and challenges of integrating ROS2 into industrial robotics. It also shows how advanced perception algorithms can enable faster and more reliable of metallic objects.
The SwRI maintains the ROS-industrial software repository and manages the ROS-industrial consortium. Consortia members in the Americas, Europe, and Asia drive new capabilities in ROS-I by championing focused projects based on their near-term requirements.
Originally posted 2019-04-12 17:33:19.
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