Skip to main navigation Skip to search Skip to main content

Thruster-Assisted Incline Walking of a Legged-Aerial Robot Using Reduced Order Model and Collocation Method

  • Kaushik Venkatesh Krishnamurthy
  • , Chenghao Wang
  • , Shreyansh Pitroda
  • , Adarsh Salagame
  • , Eric Sihite
  • , Reza Nemovi
  • , Alireza Ramezani
  • , Morteza Gharib

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

Abstract

In this study, our aim is to evaluate the effectiveness of thruster-assisted steep slope walking for the Husky Carbon, a quadrupedal robot equipped with custom-designed actuators and plural electric ducted fans, through simulation prior to conducting experimental trials. Thruster-assisted steep slope walking draws inspiration from wing-assisted incline running (WAIR) observed in birds, and intriguingly incorporates posture manipulation and thrust vectoring, a locomotion technique not previously explored in the animal kingdom. Our approach involves developing a reduced-order model of the Husky robot, followed by the application of an optimization-based controller utilizing collocation methods and dynamics interpolation to determine control actions. Through simulation testing, we demonstrate the feasibility of hardware implementation of our controller.

Original languageEnglish (US)
Title of host publication2025 American Control Conference, ACC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3738-3743
Number of pages6
ISBN (Electronic)9798331569372
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 American Control Conference, ACC 2025 - Denver, United States
Duration: Jul 8 2025Jul 10 2025

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2025 American Control Conference, ACC 2025
Country/TerritoryUnited States
CityDenver
Period7/8/257/10/25

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Thruster-Assisted Incline Walking of a Legged-Aerial Robot Using Reduced Order Model and Collocation Method'. Together they form a unique fingerprint.

Cite this