Name: Keshav Rajasekaran

Title: Bio-Inspired flow sensors and their application in Unmanned Air Vehicles

Date: 07/22/2022

Time: 9AM – 11AM

Location: EGR 2164

Committee members:

Professor Miao Yu, Chair

Professor Sarah Bergbreiter, Co-Chair

Professor Don Devoe

Professor Nikhil Chopra 

Professor Ryan Sochol

Professor Pamela Abshire (Dean’s Representative)


Small-scale unmanned air vehicles require lightweight, compact, and low-power sensors that encompass various sensing modalities to enable flight control and navigation in challenging environments. Flow sensing is one such modality that has attracted much interest in recent years. Previously reported flow sensors are mostly fabricated by using the traditional MEMS process and have been primarily used to measure underwater flows.
The overall goal of this dissertation is to develop novel bio-inspired directional flow sensors based on additive manufacturing techniques and explore the application of directional flow sensors for use in micro air vehicles. Three major research thrusts are pursued. First, a micro-scale artificial hair sensor is developed for two-dimensional directional flow sensing. The sensor structure is fabricated by using nano-scale 3D printing, which allows high-precision fabrication with a good device to device uniformity. The performance of the sensor is thoroughly studied in deflection experiments with a probe station and in airflow tests.  
The sensor is integrated with a micro air vehicle (MAV), and detection of flow separation is demonstrated. Second,  flow detection on MAVs with a pair of all elastomer strain sensors is investigated. The soft flow sensors are integrated with an MVA, and the abilities of the sensors for obstacle and gust detection are demonstrated. Finally, the use of bio-inspired flow sensors on a micro air vehicle for performing simple control tasks is explored. The experimental results demonstrate that the sensors are capable of early disturbance warnings, and the sensor output can be used to perform simple navigation tasks, for example, following a wall.