Comau Introduces MI.RA/OnePicker, A New And Fully Automated Intelligent Piece Picking Solution
-The easy-to-use, AI-backed and collaborative solution reduces upstream process times, saving time, energy and resources for warehouse, e-commerce and other diversified applications while increasing overall productivity and cost efficiency
-Vision-based piece picking autonomously grasps randomly placed heterogeneous objects
-Can be installed on even the smallest collaborative robots without limiting its reachability inside the bins
Comau unveils the newest solution in its Machine Inspection Recognition Archetypes (MI.RA) family of hardware-agnostic, intelligent vision systems, MI.RA/OnePicker. Making its worldwide debut at Automate 2024, North America’s leading automation show, Comau’s new perception-based piece picking solution is the easy and smart way to eliminate unsustainable sorting activities within diversified industries, which in turn increases both worker well-being and overall efficiency. Enhanced with Artificial Intelligence, the hardware agnostic solution pairs state-of-the-art vision technology with advanced sensors to pick randomly displaced objects after calculating the picking pose in mere seconds. The compact and lightweight robot vision guidance system proactively determines the most effective way to empty a bin while saving costs and lowering potential risks.
MI.RA/OnePicker is designed to autonomously pick miscellaneous objects from the same bin without relying on CAD-based assistance or prior information about their size, shape, color or characteristics. AI-enabled and adaptable to any brand of commercial robot, customized bin or customized gripper, the smart functionality of Comau’s newest MI.RA solution is ideal for pick&place, kitting, sorting, warehouse, e-commerce and similar applications. Thanks to streamlined virtual simulation tools and predictive algorithms that guarantee optimal path management and collision-free trajectories, Comau’s new MI.RA/OnePicker ensures unparalleled precision and reliable performance while reducing the need for costly manual and repetitive operations.
“MI.RA/OnePicker is a result of our continued efforts to make complex technology more accessible and effective for a diverse range of industries.” said Nicole Clement, Chief Business Unit Leader for Advanced Automation Solutions. “Comau’s dedication to powering automation for companies of all sizes with intelligent robotic solutions now extends to complex piece picking operations in industries such as warehousing and manufacturing, among others. This is a market, based on our internal estimates and supporting research, that is expected to achieve a compound annual growth rate of 76% (2019-2025).”
Comau’s systems-based approach to flexible automation allows the company to offer powerful turn-key solutions that are increasingly easy to use. Leveraging proprietary automation and machine learning paradigms, MI.RA/OnePicker has a highly intuitive configuration page from which customers can easily set up the bin environment and parameter specifics. From the user-defined 3D models of the bin, the environment and the robot, the integrated algorithms can calculate the ideal balance between computational speed and accuracy. Furthermore, the neural network autonomously recognizes the surfaces from which an object can be picked using a suction cup to facilitate identification of the most suitable grasping points. As a result, MI.RA/OnePicker can guarantee efficient path planning and collision-free movements in complete safety while ensuring optimal piece picking performance by the robot.
As an all-in-one-system, MI.RA/OnePicker comes with Comau’s Racer5 COBOT, a 6-axis articulated robot that delivers speed, accuracy, repeatability, and certified collaboration safety without cages. Because the compact COBOT can automatically switch from industrial mode to collaborative mode, working at full speeds when human operators are not in the vicinity and at collaborative speeds when they are, productivity remains high and cycle times are reduced.
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