Aerial assistive payload transportation using quadrotor UAVs with nonsingular fast terminal SMC for human physical interaction

This paper presents a novel approach to utilizing underactuated quadrotor Unmanned Aerial Vehicles (UAVs) as assistive devices in cooperative payload transportation task through human guidance and physical interaction. The proposed system consists of two underactuated UAVs rigidly connected to the transported payload. This task involves the collaboration between human and UAVs to transport and manipulate a payload. The goal is to reduce the workload of the human and enable seamless interaction between the human operator and the aerial vehicle. An Admittance-Nonsingular Fast Terminal Sliding Mode Control (NFTSMC) is employed to control and asymptotically stabilize the system while performing the task, where forces are applied to the payload by the human operator dictate the aerial vehicle's motion. The stability of the proposed controller is confirmed using Lyapunov analysis. Extensive simulation studies were conducted using MATLAB, Robot Operating System (ROS), and Gazebo to validate robustness and effectiveness of the proposed controller in assisting with payload transportation tasks. Results demonstrate feasibility and potential benefits utilizing quadrotor UAVs as assistive devices for payload transportation through intuitive human-guided control. • Novel assistive cooperative design for payload transportation system with human physical interaction. • Admittance controller for aerial vehicle-human physical interaction. • Chattering minimization. • Accurate tracking performance. • Asymptotic stability.

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Institutions

Publication Details

Journal
Results in Engineering
Published
2024-12-12
DOI
https://doi.org/10.1016/j.rineng.2024.103701
Citations
15
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
3.74

Funders

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article

Aerial assistive payload transportation using quadrotor UAVs with nonsingular fast terminal SMC for human physical interaction

Mojtaba Ahmadi, Hussein N. Naser, Hashim A. Hashim
15 citations
Results in Engineering
Robotic Path Planning Algorithms
3.74
article

Aerial assistive payload transportation using quadrotor UAVs with nonsingular fast terminal SMC for human physical interaction

Mojtaba Ahmadi, Hussein N. Naser, Hashim A. Hashim
article en
15 citations

Abstract

This paper presents a novel approach to utilizing underactuated quadrotor Unmanned Aerial Vehicles (UAVs) as assistive devices in cooperative payload transportation task through human guidance and physical interaction. The proposed system consists of two underactuated UAVs rigidly connected to the transported payload. This task involves the collaboration between human and UAVs to transport and manipulate a payload. The goal is to reduce the workload of the human and enable seamless interaction between the human operator and the aerial vehicle. An Admittance-Nonsingular Fast Terminal Sliding Mode Control (NFTSMC) is employed to control and asymptotically stabilize the system while performing the task, where forces are applied to the payload by the human operator dictate the aerial vehicle's motion. The stability of the proposed controller is confirmed using Lyapunov analysis. Extensive simulation studies were conducted using MATLAB, Robot Operating System (ROS), and Gazebo to validate robustness and effectiveness of the proposed controller in assisting with payload transportation tasks. Results demonstrate feasibility and potential benefits utilizing quadrotor UAVs as assistive devices for payload transportation through intuitive human-guided control. • Novel assistive cooperative design for payload transportation system with human physical interaction. • Admittance controller for aerial vehicle-human physical interaction. • Chattering minimization. • Accurate tracking performance. • Asymptotic stability.

Results in EngineeringVol. 25
Carleton University (CA)
University of Thi-Qar, Ministry of Higher Education and Scientific Research, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 5%
Robotic Path Planning Algorithms
3.74
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