Vision-less sensing for autonomous micro-drones

Simon Pikalov, Elisha Azaria, Shaya Sonnenberg, Boaz Ben-Moshe, Amos Azaria

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This work presents a concept of intelligent vision-less micro-drones, which are motivated by flying animals such as insects, birds, and bats. The presented micro-drone (named BAT: Blind Autonomous Tiny-drone) can perform bio-inspired complex tasks without the use of cameras. The BAT uses LIDARs and self-emitted optical-flow in order to perform obstacle avoiding and maze-solving. The controlling algorithms were implemented on an onboard micro-controller, allowing the BAT to be fully autonomous. We further present a method for using the information collected by the drone to generate a detailed mapping of the environment. A complete model of the BAT was implemented and tested using several scenarios both in simulation and field experiments, in which it was able to explore and map complex building autonomously even in total darkness.

Original languageEnglish
Article number5293
JournalSensors
Volume21
Issue number16
DOIs
StatePublished - 2 Aug 2021

Keywords

  • Autonomous micro-drones
  • Bio-inspired micro-robotics
  • Indoor mapping
  • Sensor fusion

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