Control, Robotics, Machine Learning

Dr. Luke A. Wendt received his B.S. in Physics and Engineering (with electrical emph.) from Hope College. While there, he designed automated part inspection systems for Lakeshore Vision and Robotics. Luke also worked at NASA’s Goddard Space Flight Center in the modeling, control, and construction of a reconfigurable tetrahedral rover. Luke received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, emphasizing in control theory, robotics, and machine learning. While at Illinois, Luke was a member of the Language Acquisition and Robotics Group. At Beckman, he researched embodied cognition on the iCub, a humanoid robotics platform from the Italian Institute of Technology. He has contracted for Valve Software in the design of sensor fusion systems for head mounted VR tracking. Luke has instructed many courses and labs including the robotics and control labs and the senior design lab. He has mentored undergraduates. He has had leadership roles with the NASA academies and FIRST Robotics. Luke worked on autonomous driving and navigation at Petronics, a robotics startup at the tech incubator in Research Park. While at Petronics, he developed an AR control interface with integrated sensor fusion and map building, multi-session SLAM with a monocular camera and globally consistent occupancy, autonomous driving with surface-aware planning and dynamic obstacle avoidance, and motion stabilization for a mobile 360 camera. He also co-wrote and won an SBIR grant for over $1M. Luke's most recent work was with Sententia. He worked with Jeremy Adsitt to build a cloud document classification pipeline and built image to text services with Tesseract and text and image classifiers using TensforFlow.

Research Interests

  • Control

    • Model Predictive Control

  • Robotics

    • Ag Robotics

    • Soft Robotics

    • Walking Robotics

    • Self-Driving Robotics

    • Bio-Inspired Robotics

  • Machine Learning

    • Generative Adversarial Networks

    • Recurrent Neural Networks

    • Variational Autoencoders

    • Deep Learning

  • VR/AR

    • 6DOF Video