Project description
The future of autonomous UAV swarm navigation
Robotics have seen remarkable progress, particularly in the development of small Unmanned Aerial Vehicles (UAVs) capable of autonomous, vision-based flights. These advances have fuelled interest in various applications, from drone delivery to infrastructure inspection. However, current solutions face limitations in terms of robustness and adaptability, hindering their performance in challenging, uncontrolled environments. The ERC-funded SkEyes project is set to change this narrative. With a decade of experience in the field, SkEyes aims to harness cutting-edge sensors, including lidar, depth, thermal, event, and visual cameras, to enable a swarm of small UAVs to collaborate effectively. By combining these heterogeneous sensing cues, SkEyes intends to enable intelligent UAV swarm navigation in critical scenarios such as wildfires.
Objective
Over the past two decades, we witnessed impressive advancements in Robotics. Amongst the most disruptive developments was the demonstration of small Unmanned Aerial Vehicles (UAVs) equipped with onboard cameras conducting autonomous, vision-based flights without reliance on GPS, sparking booming interest in a plethora of use-cases, such as automation of drone delivery, and infrastructure inspection and maintenance. This led to the emergence of new algorithms, advanced sensors, as well as miniaturized, powerful chips, opening exciting opportunities for automating single- as well as multi-UAV navigation. Current solutions, however, lack greatly in robustness and generality, struggling to perform outside very controlled settings, with onboard perception constituting the biggest impediment.
Working in this area for over a decade, it is troubling that despite dramatic progress, we still lack the technology to enable a UAV swarm to autonomously scan the seas for refugee dinghies or forest areas for wildfires, and to provide help in such dire situations. While, in principle, the core technology is the same across all use-cases, battling adverse conditions, such as wind, smoke, and degraded illumination, render the latter use-cases extremely challenging as they are time-critical and cannot be postponed until favorable conditions arise. Employing some of the currently most promising sensors, such as lidar, and advanced depth, thermal, event, and visual cameras, SkEyes proposes to address fundamental research questions to understand how to process and combine these heterogeneous sensing cues onboard a swarm of small UAVs. The goal is to achieve joint spatial understanding and scene awareness for effective autonomy in highly dynamic and realistic scenarios. Engaging such eyes in the sky, the focus is on robust, collaborative perception to enable intelligent UAV swarm navigation exhibiting adaptability in completing a mission in challenging conditions, at the push of a button.
Fields of science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- social sciencessociologyindustrial relationsautomation
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdrones
- social sciencessociologydemographyhuman migrations
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
1678 Nicosia
Cyprus