Airflow Source Seeking on Small Quadrotors Using a Single Flow Sensor

TL;DR

This work demonstrates a compact, flow-vector sensing approach on a sub-100 g quadrotor to complement chemical plume tracking. By integrating a 2D flow sensor and a bio-inspired Vector Surge algorithm, the system can detect airflow direction, reorient toward the flow, and perform in-plane source-seeking from random initial poses. Key contributions include hardware integration on a palm-sized UAV, real-time 2D flow-angle and magnitude estimation in flight, and a cast-and-surge control loop that leverages flow direction to locate airflow sources. The results show reliable angle estimation down to $0.2~\mathrm{m s^{-1}}$ and rapid reorientation, laying the groundwork for richer plume tracking when combined with onboard or directional chemical sensors in constrained environments.

Abstract

As environmental disasters happen more frequently and severely, seeking the source of pollutants or harmful particulates using plume tracking becomes even more important. Plume tracking on small quadrotors would allow these systems to operate around humans and fly in more confined spaces, but can be challenging due to poor sensitivity and long response times from gas sensors that fit on small quadrotors. In this work, we present an approach to complement chemical plume tracking with airflow source-seeking behavior using a custom flow sensor that can sense both airflow magnitude and direction on small quadrotors < 100 g. We use this sensor to implement a modified version of the `Cast and Surge' algorithm that takes advantage of flow direction sensing to find and navigate towards flow sources. A series of characterization experiments verified that the system can detect airflow while in flight and reorient the quadrotor toward the airflow. Several trials with random starting locations and orientations were used to show that our source-seeking algorithm can reliably find a flow source. This work aims to provide a foundation for future platforms that can use flow sensors in concert with other sensors to enable richer plume tracking data collection and source-seeking.

Figures (10)

• Figure 1: (a) A flying DJI Tello quadrotor with the flow sensor mounted on top. (b) Exploded view of the flow sensor and quadrotor mount.
• Figure 2: The quadrotor coordinate system and a representation of the angle, $\theta$, that defines the error between the quadrotor heading (0°) and the upwind direction.
• Figure 3: The four measurement locations and their respective distances and average airflow speed measured by an anemometer. The fan was fixed at a height of 1 m off the ground, level with the quadrotor's height in the air.
• Figure 4: Behavior of the quadrotor using the Vector Surge algorithm.
• Figure 5: Flowchart depicting each state in Vector Surge and each respective operation.