Computer Science and Engineering, Department of
Date of this Version
Unmanned aerial vehicles (UAVs) are playing an increasing role in large scale environmental monitoring. Small UAVs are increasingly used to monitor agricultural fields, infrastructure projects, and disaster areas. The combination of their sensors, ease of use, and portability make them an ideal tool for collecting information on demand about geographic regions. These small UAVs do have several significant limitations. The UAVs have very limited autonomy and fly pre-determined flight paths far above the underlying terrain, limiting the spatial resolution of the collected data. Current battery technology severely limits their flight times, which in turn limits the temporal resolution of the data collection processes. What all users, from farmers to first responders, require are improved systems with higher levels of autonomy for long term environmental monitoring.
Our research uses two complementary approaches to address these limitations in autonomy and endurance. Our first contribution introduces novel techniques for localizing small UAVs in outdoor environments. These improved localization techniques allow the vehicle to operate within one meter of mature agricultural fields throughout the growing season. Improved localization not only improves the vehicles' autonomy, but it also increases the spatial resolution of data collected from the airborne vehicles.
We complement the short term near earth sensing capabilities by deploying long lasting wireless sensor network (WSN) nodes from the same small UAVs. We improve upon traditional WSN deployment mechanisms by performing tactile surface classification from the UAV prior to deploying a node. This pre-deployment procedure changes haphazard sensor deployments to controlled installations, which improves deployment outcomes. The UAVs also performs a post-deployment assessment of the installation outcome, enabling preemptive replacement or maintenance of ineffective nodes.
These complementary approaches exploit the high mobility and powerful sensors of small UAVs with energy efficient and long lasting WSNs to maximize the information collected from the environment. Our localization techniques improve the autonomy and capabilities of small UAVs in agricultural and other complex outdoor environments. Our work on WSN deployments bridges the gap between the WSN and robotics communities to create comprehensive environmental monitoring capabilities that use the strengths of both groups.
Adviser: Carrick Detweiler
A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy, Major: Engineering, Under the Supervision of Carrick Detweiler, Lincoln, Nebraska: December, 2016