MEMS Airflow Sensors for Model-Based UAV Control in Extreme Wind Conditions
Abstract
Autonomous unmanned aerial vehicles (UAVs) have potential for transformative impact in a variety of military and civilian domains including infrastructure inspection and repair, remote search-and-rescue, aerial package delivery, and urban air mobility. Within the Air Force, initiatives such as Agility Prime, Golden Horde, and Loyal Wingman seek to leverage UAV autonomy to bring about new capabilities. However, operation in such domains requires UAVs to perform reliably in extreme wind environments: from harsh offshore conditions to gusts in the urban canopy. Current systems do not meet this criterion; the maximum safe wind speed for a typical commercial multirotor UAV is around 20 mph. Multirotor vehicles are rarely equipped to measure flow speed directly; rather, they infer a wind estimate from the control inputs required to maintain setpoints. This reliance on indirect wind assessment (rather than direct direction –dependent measurements) is due to the limitations of available sensor technology; existing flow sensors (such as pitot tubes, hot wire, and ultrasonic anemometers) lack the speed, sensitivity, or form-factor for successful integration onto multirotor platforms.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 21, 2022
- Source ID
- FA95502210020XX0
Entities
People
- Anirudha Majumdar
Organizations
- Air Force Office of Scientific Research
- Trustees of Princeton University
- United States Air Force