Demo Abstract: Towards Reliable Obstacle Avoidance for Nano-UAVs
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Author / Producer
Date
2022-01
Publication Type
Other Conference Item
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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.
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Publication status
published
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Editor
Book title
2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
Journal / series
Volume
Pages / Article No.
501 - 502
Publisher
IEEE
Event
21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2022)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
UAV; nano-UAV; obstacle avoidance; autonomous navigation
Organisational unit
03996 - Benini, Luca / Benini, Luca