JPL: Rapid forest triage using quadcopter drones

In collaboration with Roland Brockers at JPL and Kelly Caylor of Princeton CEE, we were funded to develop capabilities to use a small quadrotor UAV that navigates fully autonomously under tree canopy to perform in-situ sensing for forest monitoring applications.

JPL is developing onboard image processing (computer vision) for determining the geometry of a scene, and choosing an optimal path to reach a target.  We will supplement these algorithms with additional cameras that would record sequential images that can be post-processed to determine the sizes and shapes of trees along the drone’s path. Additionally, we developed electronics to monitor microclimate within the canopy, to investigate covariance of forest structure with microclimate.

Princeton’s Grand Challenges program will fund two undergrads to participate in this work and take the lead in developing the computer vision algorithms and microclimate measurements.