CapSen Robotics
Canvas Category Machinery : Industrial Robot : Piece Picking
CapSen Robotics is a company that develops software to identify, scan, and track the 3D positions and orientations of specific objects in cluttered scenes. Its CapSen PiC solution combines 3D vision technology and motion planning intelligence to perform object detection, motion planning, and collision avoidance.
Assembly Line
AFRL successfully field-tests AI robot to improve DAF manufacturing capability
Researchers from the Air Force Research Laboratory, or AFRL, have combined efforts with The Ohio State University, or OSU, and industry partners CapSen Robotics and Yaskawa Motoman to successfully demonstrate an autonomous robotic incremental metal forming prototype at the Warner-Robins Air Logistics Complex, or WR-ALC, a tenant of Robins Air Force Base in Georgia, in late January 2023. The artificially intelligent system, nicknamed AI-FORGE, was funded primarily by the Advanced Robotics for Manufacturing, or ARM, Institute, and promises to not only improve aircraft readiness for the U.S. Department of the Air Force but also to significantly impact the future of metamorphic manufacturing, also called robotic blacksmithing.
“There is an immediate need to obtain customized forged components that we might only require a few of, but which have significant lead times,” said Dr. Sean Donegan, digital manufacturing research team lead, AFRL’s Materials and Manufacturing Directorate. “In the near future, this system will allow us to acquire the specific auxiliary components and tools that are required to successfully support DAF missions. But in the far term, we want to be able to make almost anything.
AI-FORGE uses incremental forming, a heat-assisted metalworking process that permits users to manufacture small lots of customized manufactured parts for military aircraft. The addition of artificially intelligent software allows the robotic system to make significant forming decisions on its own without the need for a human operator, offering near-term cost- and time-saving benefits as well as an improved ability to replace hard-to-find aircraft structural parts. ”
3D Vision Technology Advances to Keep Pace With Bin Picking Challenges
When a bin has one type of object with a fixed shape, bin picking is straightforward, as CAD models can easily recognize and localize individual items. But randomly positioned objects can overlap or become entangled, presenting one of the greatest challenges in bin picking. Identifying objects with varying shapes, sizes, colors, and materials poses an even larger challenge, but by deploying deep learning algorithms, it is possible to find and match objects that do not conform to one single geometrical description but belong to a general class defined by examples, according to Andrea Pufflerova, Public Relations Specialist at Photoneo.
“A well-trained convolutional neural network (CNN) can recognize and classify mixed and new types of objects that it has never come across before,”