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Datum
2022-01Typ
- Other Conference Item
ETH Bibliographie
yes
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Abstract
Unmanned aerial vehicles (UAVs) are a very active research topic, and especially the nano and micro subclass, characterized by centimeter size and minimal on-board computational capabilities, have gained popularity in recent years. These lightweight platforms provide good agility and movement freedom in indoor environments, but it is still a significant challenge to enable autonomous navigation or basic obstacle avoidance capabilities using standard image sensors, due to the limited computational capabilities that can be hosted on-board. This work demonstrates the possibility of using a new multi-zone Time of Flight (ToF) sensor to enhance autonomous navigation with a significantly lower computational load than most common visual-based solutions. Our system proved reliable (>95%) in-field obstacle avoidance capabilities when flying in indoor environments with dynamic obstacles. Mehr anzeigen
Publikationsstatus
publishedExterne Links
Buchtitel
2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)Seiten / Artikelnummer
Verlag
IEEEKonferenz
Thema
UAV; nano-UAV; obstacle avoidance; autonomous navigationOrganisationseinheit
03996 - Benini, Luca / Benini, Luca
ETH Bibliographie
yes
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