UAV Control in Close Proximities - Ceiling Effect on Battery Lifetime

With the recent developments in the unmanned aerial vehicles (UAV), it is expected them to interact and collaborate with their surrounding objects, other robots and people in order to wisely plan and execute particular tasks. Although these interaction operations are inherently challenging as compared to free-flight missions, they might bring diverse advantages. One of them is their basic aerodynamic interaction during the flight in close proximities which can result in a reduction of the controller effort. In this study, by collecting real-time data, we have observed that the current drawn by the battery can be decreased while flying very close to the surroundings with the help of the ceiling effect. For the first time, this phenomenon is analyzed in terms of battery lifetime degradation by using a simple full equivalent cycle counting method. Results show that cycling related effect on battery degradation can be reduced by a 15.77% if the UAV can utilize ceiling effect.Comment: ICoIAS 201

Learning tethered perching for aerial robots

Aerial robots have a wide range of applications, such as collecting data in hard-to-reach areas. This requires the longest possible operation time. However, because currently available commercial batteries have limited specific energy of roughly 300 W h kg -1 , a drone's flight time is a bottleneck for sustainable long-term data collection. Inspired by birds in nature, a possible approach to tackle this challenge is to perch drones on trees, and environmental or man-made structures, to save energy whilst in operation. In this paper, we propose an algorithm to automatically generate trajectories for a drone to perch on a tree branch, using the proposed tethered perching mechanism with a pendulum-like structure. This enables a drone to perform an energy-optimised, controlled 180° flip to safely disarm upside down. To fine-tune a set of reachable trajectories, a soft actor critic-based reinforcement algorithm is used. Our experimental results show the feasibility of the set of trajectories with successful perching. Our findings demonstrate that the proposed approach enables energy-efficient landing for long-term data collection tasks

Autonomous Drone-Based Sensor Package Deployment to the Underside of Structures

The objective of this project is to design, develop and experimentally test an Unmanned Aircraft System (UAS, commonly known as a drone) for the deployment of sensor packages to the underside of structures. This work begins with an in-depth review of existing automation techniques for various drone applications focusing on applications requiring interaction with the environment. Further reviewed is the impact of structures above the UAS during flight on the behavior of the aircraft. Considering these topics, the development of a custom drone is presented to address the difficulties of delivering a package to the underside of a structure. Starting with manual flights, the drone is piloted by a human operator to serve as proof of concept of the drone’s ability to navigate under the ceiling effect and make contact with the underside of the structure. During the manual flight experiments the drone tasks increased in difficulty beginning with docking the drone without a package to the underside of a structure, delivering a package to the underside of a structure, and finally retrieving that package. Finally, the development of a vision-based navigation system is presented to autonomously perform the same tasks. The system is validated through a series of autonomous flight experiments using the OptiTrack motion capture system and ArUco fiducial markers for onboard localization. The autonomous tasks successfully completed and presented in this work support the proposed use of drones for deploying sensor packages to the underside of structures, even in GPS denied environments