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AGILEFLIGHT

Financiado

Cerrado

Low latency Perception and Action for Agile Vision based Flight

Drones are disrupting industries, such as agriculture, package delivery, inspection, and search and rescue. However, they are still either controlled by a human pilot or heavily rely on GPS for navigating autonomously. The alterna... ver más

31/08/2025

UZH

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

UNIVERSITAT ZURICH No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-02-07

ERC-2019-COG: ERC Consolidator Grant

I+D

Cerrada hace 5 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

UZH

2.00M€ | Lider

GRUPO TTT DE TECNOLOGIAS INT...

629.40K€ | Participante

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Duración del proyecto: 66 meses Fecha Inicio: 2020-02-07
Fecha Fin: 2025-08-31

Líder del proyecto

UNIVERSITAT ZURICH No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Drones are disrupting industries, such as agriculture, package delivery, inspection, and search and rescue. However, they are still either controlled by a human pilot or heavily rely on GPS for navigating autonomously. The alternative to GPS are onboard sensors, such as cameras: from the raw data, a local 3D map of the environment is built, which is then used to plan a safe trajectory to the goal. While the underlying algorithms are well understood, we are still far from having autonomous drones that can navigate through complex environments as good as human pilots. State-of-the-art perception and control algorithms are mature but not robust: coping with unreliable state estimation, low-latency perception, real-time planning in dynamic environments, and tight coupling of perception and action under severe resource constraints are all still unsolved research problems. Another issue is that, because battery energy density is increasing at a very slow rate, drones need to navigate faster in order to accomplish more within their limited flight time. To obtain more agile robots, we need faster sensors and low-latency processing. The goal of this project is to develop novel scientific methods that would allow me to demonstrate autonomous, vision-based, agile quadrotor navigation in unknown, GPS-denied, and cluttered environments with possibly moving obstacles, which can be as effective in terms of maneuverability and agility as those of professional drone pilots. The outcome would not only be beneficial for disaster response scenarios, but also for other scenarios, such as aerial delivery or inspection. To achieve this ambitious goal, I will first develop robust, low-latency, multimodal perception algorithms that combine the advantages of standard cameras with event cameras. Then, I will develop novel methods that unify perception and state estimation together with planning and control to enable agile maneuvers through cluttered, unknown, and dynamic environments.

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