Human-Machine Cooperative Control of UAV in Complex Indoor Environments

Jiawen Ding, Ying Liu, Luzheng Bi, Aberham Genetu Feleke, Weijie Fei*

*Corresponding author for this work

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

Abstract

Unmanned aerial vehicle (UAV), as a current research hotspot, has a vast potential application prospect in military and civilian sectors, and it helps to deal with the coping ability of dangerous and complex scenes.Most of the UAVs based on autonomous control systems or manual control have poor adaptability to complex environments and weak anti-interference ability, which limits the application scope of UAVs.In this paper, authority allocation is applied to the control system of UAV, and the UAV system based on human-machine authority allocation is constructed by combining manual control with model predictive control (MPC).The performance of the system is verified through UAV simulation experiments.The experimental results show that human-machine collaborative control performs better than the manual control in terms of average completion time and collision rate, and the proposed system can improve the safety of the UAV control, and at the same time enhance the task completion efficiency of the UAV system.

Original languageEnglish
Title of host publicationProceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
EditorsRong Song
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1722-1726
Number of pages5
ISBN (Electronic)9798350384185
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Unmanned Systems, ICUS 2024 - Nanjing, China
Duration: 18 Oct 202420 Oct 2024

Publication series

NameProceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024

Conference

Conference2024 IEEE International Conference on Unmanned Systems, ICUS 2024
Country/TerritoryChina
CityNanjing
Period18/10/2420/10/24

Keywords

  • authority allocation
  • human-machine collaboration
  • MPC
  • UAV

Cite this