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Tail-MAV: Design and Control of a Perching Micro Aerial Vehicle Inspired by the tail-suspended behavior of primates

  • Ye Li
  • , Dongyang Li
  • , Yitian Zhang
  • , Liewei Huang
  • , Siqi Wang
  • , Bo Cai*
  • *Corresponding author for this work
  • School of Astronautics, Harbin Institute of Technology
  • China Aerospace Science and Industry Corporation

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

Abstract

To address the challenge of achieving rapid, stable, and passively triggered perching in complex environments without requiring precise alignment, a bioinspired micro air vehicle named Tail-MAV is developed. The system features a bistable mechanism that mimics the tail-hanging behavior of primates, enabling attachment within 100 milliseconds. An adaptive back- stepping controller integrated with a dual-time-scale disturbance observer (AB-DTDO) is then designed to enhance control performance during dynamic flight and perching through real-time disturbance estimation and compensation. Experimental results demonstrate that Tail-MAV achieves reliable perching across diverse substrates and exhibits improved trajectory tracking during agile flight. Compared with the LADRC and PID controllers respectively, the AB-DTDO method reduces the average tracking error by 22.3% and 47.6% respectively, significantly improving the control accuracy and robustness.

Original languageEnglish
Title of host publication2025 7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages372-376
Number of pages5
ISBN (Electronic)9798331574703
DOIs
StatePublished - 2025
Externally publishedYes
Event7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025 - Changzhou, China
Duration: 12 Dec 202514 Dec 2025

Publication series

Name2025 7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025

Conference

Conference7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025
Country/TerritoryChina
CityChangzhou
Period12/12/2514/12/25

Keywords

  • MAV
  • adaptive backstepping controller
  • disturbance observe
  • dual-time-scale
  • perching

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