Digitizing Construction with AI

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Roboticist by training with expertise in computer vision, machine learning and manipulation, CTO and co-founder of Scaled Robotics. At Scaled Robotics, he leads a team that has developed pioneering solutions for complex 3D perception and classification problems in highly unstructured construction environments. His research interests include applying statistical learning techniques to perception and control problems in the fields of 3D vision, active perception and interactive perception.
Background: PhD from the University of Southern California, ex-research assistant at the GRASP Lab at the University of Pennsylvania, the Robotics Institute at Carnegie Mellon, and the Space Systems Lab at the University of Maryland. To know more about Dr. Sankaran check his page.

Underlying most of the construction’s problems is the simple fact that there is no quick and reliable way to compare what was designed to what is being built. This disconnect between physical reality and digital design leads to very inefficient process control. At Scaled Robotics, experts leverage state-of-the-art machine learning and robotics to build new tools that can track, analyze and optimize construction processes, thereby reducing waste and inefficiency. From this talk, you will learn how Scaled Robotics specialists provide highly accurate and precise quality control and progress information on complex construction projects using 3D computer vision, 3D machine learning, and nonlinear optimization. Deep understanding of techniques in 3D to solve complex real-world problems significantly how reality diverges from research.


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