A Vision-Based Motion Control Framework for Water Quality Monitoring Using an Unmanned Aerial Vehicle

Abstract

In this paper, we present a vision-aided motion planning and control framework for the efficient monitoring and surveillance of water surfaces using an Unmanned Aerial Vehicle (UAV). The ultimate goal of the proposed strategy is to equip the UAV with the necessary autonomy and decision-making capabilities to support First Responders during emergency water contamination incidents. Toward this direction, we propose an end-to-end solution, based on which the First Responder indicates visiting and landing waypoints, while the envisioned strategy is responsible for the safe and autonomous navigation of the UAV, the refinement of the way-point locations that maximize the visible water surface area from the onboard camera, as well as the on-site refinement of the appropriate landing region in harsh environments. More specifically, we develop an efficient waypoint-tracking motion-planning scheme with guaranteed collision avoidance, a local autonomous exploration algorithm for refining the way-point location with respect to the areas visible to the drone’s camera, water, a vision-based algorithm for the on-site area selection for feasible landing and finally, a model predictive motion controller for the landing procedure. The efficacy of the proposed framework is demonstrated via a set of simulated and experimental scenarios using an octorotor UAV.

UAV-Based Subsurface Data Collection Using a Low-Tech Ground-Truthing Payload System Enhances Shallow-Water Monitoring

“…Once the underwater camera stops detecting the habitat of interest in one direction or records a depth above or below a preset value, the flight path can automatically be adjusted to encircle the area of interest while saving valuable survey time, increasing the amount of class-specific point observations and reducing the amount of noise in the collected data set. This approach of dynamic and intelligent autonomous flight navigation and data collection has been tested in many applications [64][65][66][67] and could likewise increase the efficiency of area-based monitoring missions by, for example, limiting the data collection to areas where the UAV mounted sensor still receives useful information and at the same time indicating where subsurface data collection is required.…”