Visual Safety of Robot Networks based on Control Barrier Functions with Spherical Obstacles

Junya Yamauchi*, Reita Maeno, Tesshu Fujinami, Marco Omainska, Masayuki Fujita

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper addresses the target pursuit task by multiple mobile robots equipped with visual sensors in an environment with spherical obstacles. First, we define a target as visible to a robot when feature points on the target are inside the robot's field of view and are not occluded by an obstacle. To formulate this visibility, we derive safe sets for maintaining the field of view and for avoiding occlusion. Next, in order to achieve visibility of the robot network, we propose two methods for online visibility determination based on the mixed integer programming and the dynamic average consensus algorithm. Finally, the effectiveness of the proposed method is verified by simulation.

Original languageEnglish
Title of host publication2023 62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1090-1095
Number of pages6
ISBN (Electronic)9784907764807
DOIs
StatePublished - 2023
Event62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023 - Tsu, Japan
Duration: 2023/09/062023/09/09

Publication series

Name2023 62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023

Conference

Conference62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023
Country/TerritoryJapan
CityTsu
Period2023/09/062023/09/09

Keywords

  • control barrier function
  • rigid body motion
  • safe control
  • vision-based control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Automotive Engineering
  • Control and Systems Engineering
  • Control and Optimization
  • Instrumentation

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