Funding Source: University of Stuttgart
Motivation: Lighter-than-air vehicles (LTAVs) such as rigid and nonrigid dirigibles, or airships, are clearly a superior choice for some applications like wildlife monitoring, sports event capture and continuous patrolling of forest regions for anti-poaching tasks. LTAVs are uniquely suited as aerial communication relays, for wildlife monitoring and conservation tasks, which we address in one of our other projects, WildCap. Airships produce little noise, have high energy efficiency and long flight times, display benign collision and crash characteristics, pose low danger and cause little environmental impact. However, their comparably high handling complexity, size, lifting gas requirements and cost create an entry barrier for researchers. Unlike for heavier-than-air drones, there have been no off the shelf flight controllers that support autonomous dirigible flight. Therefore, guidance and control algorithms have to be implemented for each vehicle - even though various suitable control strategies can be found in the literature. Similar to both rotor craft and fixed wing UAVs, dirigibles come in many types of actuator arrangements: Fixed or vectoring main thrusters, differential thrust, different tail fin arrangements and auxiliary thrusters, single or double hull, etc. Thus, a control algorithm for a specific vehicle might not always be applicable to others.
Goals and Objectives:
In project AeRoShip our goal is to develop a team autonomous airships which is capable of monitoring wildlife for long durations. To this end, our objectives are
 Price, E., Liu, Y. T., Black, M. J., & Ahmad, A. (2022). Simulation and Control of Deformable Autonomous Airships in Turbulent Wind. In M. H. Ang Jr, H. Asama, W. Lin, & S. Foong (Hrsg.), Intelligent Autonomous Systems 16 (S. 608--626). Springer International Publishing. https://doi.org/10.1007/978-3-030-95892-3_46
 Liu, Y.T., Price, E., Black, M.J., Ahmad, A. (2022) Deep Residual Reinforcement Learning based Autonomous Blimp Control, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2022.