Design and Validation of Flexible Aerial Robotics for Safe Human-Robot Interaction

This work addresses the critical challenge of integrating drones into human-aerial robot interaction by presenting a novel Soft Flexible Aerial Robotics (SFAR) design. SFAR features an innovative low-pressure inflatable airbag structure that replaces traditional rigid frames, enhancing safety by mitigating collision risks with humans and payloads. To control this unconventional aerial platform, we present a control strategy based on a virtual link dynamics model that exploits the drone’s unique design. Our contributions include the pioneering design of an aerial robot specifically for Human-Aerial Robot Interaction (HARI), a novel control framework that balances flight performance with passive safety, and the validation of SFAR through real-world experiments, demonstrating its ability to perform at par with traditional rigid-body drones while offering enhanced safety features for seamless and safe integration into human environments.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801991
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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article

Design and Validation of Flexible Aerial Robotics for Safe Human-Robot Interaction

C. H. Li, Adam Rushworth, Xiaoying Yang, Salman Ijaz et al.
1 citations
Robotic Path Planning Algorithms
0.25
article

Design and Validation of Flexible Aerial Robotics for Safe Human-Robot Interaction

C. H. Li, Adam Rushworth, Xiaoying Yang, Salman Ijaz, Fuhua Jia, Rui Li, Junhao Xiao, Zihao Zheng
article en
1 citations

Abstract

This work addresses the critical challenge of integrating drones into human-aerial robot interaction by presenting a novel Soft Flexible Aerial Robotics (SFAR) design. SFAR features an innovative low-pressure inflatable airbag structure that replaces traditional rigid frames, enhancing safety by mitigating collision risks with humans and payloads. To control this unconventional aerial platform, we present a control strategy based on a virtual link dynamics model that exploits the drone’s unique design. Our contributions include the pioneering design of an aerial robot specifically for Human-Aerial Robot Interaction (HARI), a novel control framework that balances flight performance with passive safety, and the validation of SFAR through real-world experiments, demonstrating its ability to perform at par with traditional rigid-body drones while offering enhanced safety features for seamless and safe integration into human environments.

University of Nottingham Ningbo China (CN), Umeå University (SE)
Openalex Percentile: Top 43%
Robotic Path Planning Algorithms
0.25
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