Development of a Robotic Airboat for Online Water Quality Monitoring in Lakes

Abstract

Maintenance of water resources through collection of water followed by laboratory analysis, is a key factor in the measurement of water quality. The main difficulty for water collection and analysis is the logistics of the process, since the collections are often made by mall boats in very distant aquifers, applying manual processes, and are sometimes based on few samples. In this paper, the development, construction, and implementation of a robotic airboat to measure water quality in lakes has been described. The airboat was developed in the form of a mini-boat, in a fiberglass structure, whose interior housed a battery, a Raspberry Pi mini-computer, a Wi-Fi router for connection to a notebook, tablet or cell phone, and sensors connected to the Arduino platform. The airboat was validated in two lagoons in Fortaleza, and in a reservoir in the city of Pacatuba. The results were collected with the purpose of analyzing the parameters of each lagoon. The main contribution of this work was the development of an autonomous system of acquiring water parameters from several points of the lagoon.

MallARD: An Autonomous Aquatic Surface Vehicle for Inspection and Monitoring of Wet Nuclear Storage Facilities

“…When compared to previous ASVs in the literature [6][7][8][9], the tracking error achieved by the MallARD is around two orders of magnitude lower. However, it must be noted that this comparison is somewhat unfair because the MallARD is a unique ASV designed for an application that is quite dissimilar to any previously published works.…”

“…To date, a range of ASVs have been developed [6][7][8][9][10], however, most are large vehicles that have been designed for operation in marine environments and lakes [7,8,11]. They rely on unsuitable sensor packages and lack the control accuracy required for operation in SFPs or wet silos.…”

“…They rely on unsuitable sensor packages and lack the control accuracy required for operation in SFPs or wet silos. In the literature, the best performing ASVs in terms of path tracking abilities achieve an average path tracking error of around 1 m [7,8]. In [7] Dunbabin and Grinham evaluate the tracking accuracy of an autonomous surface vehicle in Lake Wivenhoe, Australia.…”

“…Previous ASVs have been underactuated [6][7][8][9][10] typically with catamaran design to maximise stability and minimise hydrodynamic drag in the surge direction. Due to the low speeds required, hydrodynamic drag magnitude will be small and since the robot must be holonomic (actuated in surge, sway and yaw) a classic catamaran design would have high drag bias in the sway direction compared to surge.…”

“…The velocity components of the state vector at index i (ẋ (i) ,ẏ (i) ,ψ (i)) are computed in real-time by numerical differentiation using current and previous readings of the displacement components (x (i) , y (i) , ψ (i)), where i is the index of the main loop as presented in Figure 4. Equation (8) gives the algorithm in terms of x, however, the algorithm is identical for y and ψ therefore their equations are once again omitted for brevity.ẋ…”