The objective of this Ph.D. thesis is the development and validation of a VTOLbased
(Vertical Take Off and Landing) micro-drone for the measurement of gas concentrations,
to locate gas emission sources, and to build gas distribution maps. Gas
distribution mapping and localization of a static gas source are complex tasks due to
the turbulent nature of gas transport under natural conditions [1] and becomes even
more challenging when airborne. This is especially so, when using a VTOL-based
micro-drone that induces disturbances through its rotors, which heavily affects gas
distribution. Besides the adaptation of a micro-drone for gas concentration measurements,
a novel method for the determination of the wind vector in real-time
is presented. The on-board sensors for the flight control of the micro-drone provide
a basis for the wind vector calculation. Furthermore, robot operating software
for controlling the micro-drone autonomously is developed and used to validate the
algorithms developed within this Ph.D. thesis in simulations and real-world experiments.
Three biologically inspired algorithms for locating gas sources are adapted and
developed for use with the micro-drone: the surge-cast algorithm (a variant of the
silkworm moth algorithm) [2], the zigzag / dung beetle algorithm [3], and a newly
developed algorithm called “pseudo gradient algorithm”. The latter extracts from
two spatially separated measuring positions the information necessary (concentration
gradient and mean wind direction) to follow a gas plume to its emission source.
The performance of the algorithms is evaluated in simulations and real-world experiments.
The distance overhead and the gas source localization success rate are used
as main performance criteria for comparing the algorithms.
Next, a new method for gas source localization (GSL) based on a particle filter
(PF) is presented. Each particle represents a weighted hypothesis of the gas source
position. As a first step, the PF-based GSL algorithm uses gas and wind measureV
ments to reason about the trajectory of a gas patch since it was released by the gas
source until it reaches the measurement position of the micro-drone. Because of the
chaotic nature of wind, an uncertainty about the wind direction has to be considered
in the reconstruction process, which extends this trajectory to a patch path envelope
(PPE). In general, the PPE describes the envelope of an area which the gas patch
has passed with high probability. Then, the weights of the particles are updated
based on the PPE. Given a uniform wind field over the search space and a single gas
source, the reconstruction of multiple trajectories at different measurement locations
using sufficient gas and wind measurements can lead to an accurate estimate of the
gas source location, whose distance to the true source location is used as the main
performance criterion. Simulations and real-world experiments are used to validate
the proposed method.
The aspect of environmental monitoring with a micro-drone is also discussed.
Two different sampling approaches are suggested in order to address this problem.
One method is the use of a predefined sweeping trajectory to explore the target
area with the micro-drone in real-world gas distribution mapping experiments. As
an alternative sampling approach an adaptive strategy is presented, which suggests
next sampling points based on an artificial potential field to direct the micro-drone
towards areas of high predictive mean and high predictive variance, while maximizing
the coverage area. The purpose of the sensor planning component is to
reduce the time that is necessary to converge to the final gas distribution model or
to reliably identify important parameters of the distribution such as areas of high
concentration. It is demonstrated that gas distribution models can provide an accurate
estimate of the location of stationary gas sources. These strategies have been
successfully tested in a variety of real-world experiments in different scenarios of gas
release using different gas sensors to verify the reproducibility of the experiments.
The adaptive strategy was also successfully validated in simulations using predefined
sweeping trajectories as reference criteria.
The results of this Ph.D. thesis reflect the applicability of gas-sensitive microdrones
in a variety of scenarios of gas release. Effective counteractive measures can
be set in motion after accidents involving gas emissions with the aid of spatially
resolved gas concentration and wind data collected with micro-drones. Monitoring
of geochemically active regions, landfills, CO2 storage facilities, and the localization
of gas leaks are further areas of application