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  • Universal Robotics Random Bin Picking

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Universal Robotics Random Bin Picking:
Universal introduces a breakthrough application – Universal Robotics Random Bin Picking. This application enables a robot to automatically move a number of randomly placed parts at typical speeds, regardless of their orientation or how deep the stack. This cost-effective breakthrough from Universal uses a suite of sensors that integrates off-the-shelf structured light sensors and pairs of cameras for stereoscopic vision. The standard application moves one part in any orientation at up to 30 per minute with standard motion control. Whether loosely or tightly packed, either on the floor, conveyor or container, the parts can be in any orientation. This application dynamically provides 3D guidance to the robot for parts regardless of the presence or type of labels or material type. It also provides accurate 3D vision guidance whether the parts are individually placed on a flat or randomly packed tightly in bin up to 48” deep. The cost effective approach eliminates expensive fixturing and automated tables, and works well under varying light conditions. Optionally, Universal’s Random Bin Picking can handle up to 3 parts in any orientation with any combined mix of SKUs per layer. Optional high-speed Sensor Servoing can further increase throughput where required. Universal Robotics has combined automated intelligence with high-speed control to enable 3D sensor input to update robot behavior in real-time. Universal’s applications integrate the best sensors and equipment with three main components to ensure measurable return on investment. Sensing (Spatial Vision Robotics). Universal engineers are experts at mixing various sensor technologies to generate accurate multi-dimensional vision guidance and inspection. Control (Autonomy). Universal’s Autonomy significantly reduces programming time of any robot, especially when optimizing throughput and accuracy of complex motion Intelligence (Neocortex). Universal’s patented Neocortex provides intelligence for operational analysis or flexible machine control in chaotic environments, enabling identification of task patterns and manipulation of never-before-seen objects.
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