Behavior tree driven multi-mobile robots via data distribution service (DDS)

Seungwoo Jeong, Taekwon Ga, Inhwan Jeong, Jongeun Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We propose multi-task programming for multi-robots via a behavior tree (BT) as a mean to reduce programming complexity of multi-mobile robots. For multi-mobile concurrent control, robot sensors or actuators data are shared via data distribution service (DDS). In addition to the advantages of DDS, the BT is deployed to control and monitor multi-mobile robots, The BTs are inherently modularized and reactive to the environments, which enables a flexible utilization of multi-mobile robots. With the help of Robot Operating System (ROS2) [1], The BTs are implemented with ROS2 nodes on the DDS that can be executed in both servers and clients for the task allocation. A simple experiment with 50kg, 100kg payload mobile robots built by Hyundai Robotics shows reliable performance with distributed BTs via DDS between servers and robots.

Original languageEnglish
Title of host publication2021 21st International Conference on Control, Automation and Systems, ICCAS 2021
PublisherIEEE Computer Society
Pages1633-1638
Number of pages6
ISBN (Electronic)9788993215212
DOIs
Publication statusPublished - 2021
Event21st International Conference on Control, Automation and Systems, ICCAS 2021 - Jeju, Korea, Republic of
Duration: 2021 Oct 122021 Oct 15

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2021-October
ISSN (Print)1598-7833

Conference

Conference21st International Conference on Control, Automation and Systems, ICCAS 2021
Country/TerritoryKorea, Republic of
CityJeju
Period21/10/1221/10/15

Bibliographical note

Funding Information:
This paper has been supported by Hyundai Robotics. All robots for testing, demonstration, as well as environmental settings, are provided in the Hyundai Robotics engineering office.

Publisher Copyright:
© 2021 ICROS.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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