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Miniature mobile robot detection using an ultra-low resolution time-of-flight sensor
ID Pleterski, Jan (Avtor), ID Škulj, Gašper (Avtor), ID Esnault, Corentin (Avtor), ID Puc, Jernej (Avtor), ID Vrabič, Rok (Avtor), ID Podržaj, Primož (Avtor)

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Izvleček
Miniature mobile robots in multi-robotic systems require reliable environmental perception for successful navigation, especially when operating in the real-world environment. One of the sensors that have recently become accessible in microrobotics due to their size and cost-effectiveness is a multi-zone time-of-flight (ToF) sensor. In this research, object classification using a convolutional neural network (CNN) based on an ultra-low resolution ToF sensor is implemented on a miniature mobile robot to distinguish the robot from other objects. The main contribution of this work is an accurate classification system implemented on low resolution, low processing power and low power consumption hardware. The developed system consists of a VL53L5CX ToF sensor with an 8x8 depth image and a low-power RP2040 microcontroller. The classification system is based on a customised CNN architecture to determine the presence of a miniature mobile robot within the observed terrain, primarily characterized by sand and rocks. The developed system trained on a custom dataset can detect a mobile robot with an accuracy of 91.8% when deployed on a microcontroller. The model implementation requires 7 kB of RAM, has an inference time of 34 ms, and an energy consumption during inference of 3.685 mJ.

Jezik:Angleški jezik
Ključne besede:miniature robots, microcontrollers, time-of-flight, convolutional neural network, binary classification, ultra-low resolution, low power, TinyML
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2023
Št. strani:9 str.
Številčenje:Vol. 72, art. 5028009
PID:20.500.12556/RUL-151584 Povezava se odpre v novem oknu
UDK:681.5:007.52
ISSN pri članku:0018-9456
DOI:10.1109/TIM.2023.3318710 Povezava se odpre v novem oknu
COBISS.SI-ID:166014211 Povezava se odpre v novem oknu
Datum objave v RUL:10.10.2023
Število ogledov:881
Število prenosov:47
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:IEEE transactions on instrumentation and measurement
Skrajšan naslov:IEEE trans. instrum. meas.
Založnik:Institute of Electrical and Electronics Engineers.
ISSN:0018-9456
COBISS.SI-ID:2861071 Povezava se odpre v novem oknu

Licence

Licenca:CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
Opis:Najbolj omejujoča licenca Creative Commons. Uporabniki lahko prenesejo in delijo delo v nekomercialne namene in ga ne smejo uporabiti za nobene druge namene.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:miniaturni roboti, mikrokrmilniki, čas preleta, konvolucijske nevronske mreže, binarna klasifikacija, ultra-nizka resolucija, nizka moč, TinyML

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