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

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

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.

• Language: English
• Keywords: miniature robots, microcontrollers, time-of-flight, convolutional neural network, binary classification, ultra-low resolution, low power, TinyML
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2023
• Number of pages: 9 str.
• Numbering: Vol. 72, art. 5028009
• PID: 20.500.12556/RUL-151584
• UDC: 681.5:007.52
• ISSN on article: 0018-9456
• DOI: 10.1109/TIM.2023.3318710
• COBISS.SI-ID: 166014211
• Publication date in RUL: 10.10.2023

Record is a part of a journal

• Title: IEEE transactions on instrumentation and measurement
• Shortened title: IEEE trans. instrum. meas.
• Publisher: Institute of Electrical and Electronics Engineers.
• ISSN: 0018-9456
• COBISS.SI-ID: 2861071

Licences

• License: CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
• Link: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Description: The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

• Language: Slovenian
• Keywords: miniaturni roboti, mikrokrmilniki, čas preleta, konvolucijske nevronske mreže, binarna klasifikacija, ultra-nizka resolucija, nizka moč, TinyML