The project progressed beyond the state of the art of aerial robotic technologies as a whole. Three WPs looked at novel technologies related to the development and use of aerial robots, their system autonomies and collaboration with humans, as well as challenges related to piloting and remote operation by non-skilled personnel.
WP1 directly addressed and investigated the main challenges of aerial manipulation. Scientific research was conducted to address challenges related to the control and stability of the platform during physical interaction with the environment, by developing novel mathematical models that represented the physics of the interaction process as accurately as possible and by addressing robustness issues as well as fluid-dynamic modeling approaches in aerial robot control. Thus, this WP addressed the limitations of existing platforms to achieve tool operation on the environment. Novel design of compliant aerial manipulators further advanced the knowledge of drone technology for safe robot-environment interaction.
WP2 aimed to develop assisted autonomy for aerial inspection tasks. Contrary to full autonomy, we investigated effective feedback between the operator, the robot, and the environment to fulfil real-world industrial monitoring. The research comprised new ways to display robotic capabilities to the user, assistance systems to help humans control the platform and understand the environment, and low-latency communication to offload computation and provide user feedback. The WP further included studies on augmented reality (AR), first-person view (FPV), and third-person view (TPV), and finally concluded that the level of assistance strongly depended on the use case. Multi-degree of freedom drone operation beyond visual line of sight in cluttered environments quickly overwhelmed the operator. Consequently, progress beyond the state-of-the-art focused on methods that would offload the sensory load by providing assisted autonomy through autonomous suggestion of optimal trajectories to the user, as well as automatic crack and corrosion detection from visual data, object-level mapping to movable objects such as valves or bricks enabling generalizable robotic object displacement. Moreover, edge computing was investigated to offload high-level computations to clusters.
WP3 focused on researching remote aerial manipulation, shared autonomy, teleoperation devices and offered services to the remote operator, robust guidance and control algorithms, communication techniques etc. Progress beyond the state of the art was achieved in edge-computing for remote control, UAV remote control under varying time delays, parametric uncertainties and payload variations, as well as disturbance rejection from wind factors and precise motion control.
