Lidar-Inertial Based Localization and Collision Avoidance in Unmanned Vehicles via Control Barrier Functions

Huai Chien Lo*, Yen Cheng Hsu, Teng Hu Cheng

*Corresponding author for this work

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

Abstract

To enhance localization reliability, we apply tightly-coupled methods that improve estimation precision through sensor integration, enabling real-time spatial awareness. To tackle realtime collision avoidance with unknown obstacles in the environment, we utilize Control Barrier Functions (CBFs) to ensure a safe distance is maintained between the vehicle and obstacles, allowing secure missions in dynamic environments. The integration of CBF with localization and path planning significantly enhances overall safety and enables real-time obstacle avoidance for unmanned vehicle navigation, particularly in scenarios with unforeseen obstacles. The proposed framework dynamically adjusts vehicle commands to avoid collisions, ensuring both reliable and safe operations. Simulations were conducted to verify the effectiveness of the developed controller.

Original languageEnglish
Title of host publication2023 International Automatic Control Conference, CACS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350306354
DOIs
StatePublished - 2023
Event2023 International Automatic Control Conference, CACS 2023 - Penghu, Taiwan
Duration: 26 Oct 202329 Oct 2023

Publication series

Name2023 International Automatic Control Conference, CACS 2023

Conference

Conference2023 International Automatic Control Conference, CACS 2023
Country/TerritoryTaiwan
CityPenghu
Period26/10/2329/10/23

Keywords

  • Collision avoidance
  • Control barrier function
  • LIDAR-inertial odometry
  • navigation

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