MIT EECS - Lincoln Laboratory Undergraduate Research and Innovation Scholar
An Energy-Efficient FPGA Vision platform for UAV navigation
Unmanned Aerial Vehicles (UAV) use a variety of imaging sensors to navigate and avoid obstacles. Real-time processing of the sensor data is necessary in order for the UAV to react quickly to changing environments; in particular, high speed vision will enable faster detection and allow more time for course correction. However, the energy available to process the data is limited as the weight of the battery must be kept to a minimum. The goal of this project is to create an energy efficient FPGA platform for vision processing on an UAV; specifically producing hardware that would fly on a real airplane using vision-based control for high-speed autonomous flight.
Having taken 6.111 and worked extensively with FPGA design and development with a concentration in processing live video, I understand the difficulties working with video in the FPGA platform. In addition, I have a passion for robotics, taking both 2.12 and 6.141, and am intrigued by the complexity of unmanned systems and understand and respect the many failure modes possible within these systems.