BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Müller, Hanna, Kartsch, Victor, Magno, Michele, Benini, Luca
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866914987355668480
author Müller, Hanna
Kartsch, Victor
Magno, Michele
Benini, Luca
author_facet Müller, Hanna
Kartsch, Victor
Magno, Michele
Benini, Luca
contents Nano-drones, distinguished by their agility, minimal weight, and cost-effectiveness, are particularly well-suited for exploration in confined, cluttered and narrow spaces. Recognizing transparent, highly reflective or absorbing materials, such as glass and metallic surfaces is challenging, as classical sensors, such as cameras or laser rangers, often do not detect them. Inspired by bats, which can fly at high speeds in complete darkness with the help of ultrasound, this paper introduces \textit{BatDeck}, a pioneering sensor-deck employing a lightweight and low-power ultrasonic sensor for nano-drone autonomous navigation. This paper first provides insights about sensor characteristics, highlighting the influence of motor noise on the ultrasound readings, then it introduces the results of extensive experimental tests for obstacle avoidance (OA) in a diverse environment. Results show that \textit{BatDeck} allows exploration for a flight time of 8 minutes while covering 136m on average before crash in a challenging environment with transparent and reflective obstacles, proving the effectiveness of ultrasonic sensors for OA on nano-drones.
format Preprint
id arxiv_https___arxiv_org_abs_2403_16696
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance
Müller, Hanna
Kartsch, Victor
Magno, Michele
Benini, Luca
Robotics
Systems and Control
Nano-drones, distinguished by their agility, minimal weight, and cost-effectiveness, are particularly well-suited for exploration in confined, cluttered and narrow spaces. Recognizing transparent, highly reflective or absorbing materials, such as glass and metallic surfaces is challenging, as classical sensors, such as cameras or laser rangers, often do not detect them. Inspired by bats, which can fly at high speeds in complete darkness with the help of ultrasound, this paper introduces \textit{BatDeck}, a pioneering sensor-deck employing a lightweight and low-power ultrasonic sensor for nano-drone autonomous navigation. This paper first provides insights about sensor characteristics, highlighting the influence of motor noise on the ultrasound readings, then it introduces the results of extensive experimental tests for obstacle avoidance (OA) in a diverse environment. Results show that \textit{BatDeck} allows exploration for a flight time of 8 minutes while covering 136m on average before crash in a challenging environment with transparent and reflective obstacles, proving the effectiveness of ultrasonic sensors for OA on nano-drones.
title BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance
topic Robotics
Systems and Control
url https://arxiv.org/abs/2403.16696