Miniature mobile robot detection using an ultra-low resolution time-of-flight sensor

Pleterski, Jan (avtor), Škulj, Gašper (avtor), Esnault, Corentin (avtor), Puc, Jernej (avtor), Vrabič, Rok (avtor), Podržaj, Primož (avtor)

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
• UDK: 681.5:007.52
• ISSN pri članku: 0018-9456
• DOI: 10.1109/TIM.2023.3318710
• COBISS.SI-ID: 166014211
• Datum objave v RUL: 10.10.2023

PLETERSKI, Jan, ŠKULJ, Gašper, ESNAULT, Corentin, PUC, Jernej, VRABIČ, Rok in PODRŽAJ, Primož, 2023, Miniature mobile robot detection using an ultra-low resolution time-of-flight sensor. IEEE transactions on instrumentation and measurement [na spletu]. 2023. Vol. 72,  5028009. [Dostopano 4 maj 2025]. DOI 10.1109/TIM.2023.3318710. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=151584

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

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

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P2-0270
• Naslov: Proizvodni sistemi, laserske tehnologije in spajanje materialov

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: L2-3168
• Naslov: Razvoj samo-učečega sistema za optimizacijo pravil vožnje avtonomnih transportnih vozil in njihovih časovno-prostorsko usklajenih aktivnosti