Please click on this link to register and connect you to the online PhD defense. Please note that the public part of the defense starts at 9.00 am, please use the above-mentioned link to join the event. Also, please be informed that Webex events are not accessible on Linux OS.
Members of the defense committee:
- Prof. Dr Jean-Régis HADJI-MINAGLOU, Université Du Luxembourg, Chairman
- Prof. Dr Radu STATE, Université Du Luxembourg, Vice-Chairman
- Prof. Dr Holger VOOS, Université Du Luxembourg, Member (Supervisor)
- Prof. Dr Fulvio MASTROGIOVANNI, Università di Genova, Member
- Prof. Dr Toshiyuki MURAKAMI, Keio University, Member
UAV teleoperation is a demanding task: to successfully accomplish the mission without collision requires skills and experience. In real-life environments, current commercial UAVs are to a large extent remotely piloted by amateur human pilots. Due to lack of teleoperation experience or skills, they often drive UAVs into collision. Therefore, in order to ensure the safety of the UAV as well as its surroundings, it is necessary for the UAV to boost the capability of detecting emergency situation and acting on its own when facing an imminent threat. However, the majority of UAVs currently available in the market are not equipped with such capability. To fill in the gap, in this work we present 2D LIDAR based Sense-and-Avoid solutions which are able to actively assist unskilled human operator in obstacle avoidance so that the operator can focus on high-level decisions and global objectives in UAV applications such as search and rescue, farming etc. Specifically, with our novel 2D LIDAR based obstacle detection and tracking algorithm, perception-assistive flight control design, progressive emergency evaluation policies and optimization-based and adaptive virtual cushion force field (AVCFF) based avoidance strategies, our proposed UAV teleoperation assistance systems are capable of obstacle detection and tracking, as well as automatic obstacle avoidance in a complex environment where both static and dynamic objects are present. Additionally, while the optimization-based solution is validated in Matlab, the AVCFF based avoidance system has been fully integrated with a sensing system, perception-assistive flight controller on the basis of the Hector Quadrotor open-source framework, and the effectiveness of the complete Sense-and-Avoid solution has been demonstrated and validated on a realistic simulated UAV platform in Gazebo simulations, where the UAV is operated at a high speed.