BrickBot and the Future of Industrial Automation
Robots need to be more easily trained and tuned to make them a viable possibility for smaller companies. Yotto Koga explains how the BrickBot is an important step forward.
For decades, only the largest companies could afford to invest the time and money necessary to set up and tune industrial robots in their facilities. In the hope of making automation more accessible for companies of all sizes, the Autodesk Research team in the Office of the CTO developed BrickBot, a robotic system that can select, position, and assemble Lego blocks using nothing more than a CAD file of the finished design. Yotto Koga, a software architect at Autodesk, explains how the BrickBot uses visual and tactile sensors and machine learning to identify and manipulate blocks, and what issues continue to pose challenges for greater access to robotics in manufacturing.
About the speaker
Yotto Koga is a software architect in the Autodesk AI Lab in the Office of the CTO. He investigates the application of deep learning techniques—including CNN, RNN, GAN, and RL—and builds smart robotic assembly systems using machine-learned vision, visual servo, and force/torque sensing strategies. He holds a PhD in Engineering from Stanford University.
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