RDL logo
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
​
​
Sign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Vision-based Autonomous Detecting and Grasping Framework for the Fully-actuated Aerial Manipulator

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2023

Vision-based Autonomous Detecting and Grasping Framework for the Fully-actuated Aerial Manipulator

0 Datasets

0 Files

en
2023
DOI: 10.1109/robio58561.2023.10354730

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Aiguo Song
Aiguo Song

Institution not specified

Verified
Shuang Hao
Guangming Song
Yue Gu
+4 more

Abstract

The Aerial Manipulator (AM) combines the flexibility of aerial platforms with the manipulative capability of manipulators. Autonomous grasping of the AM poses challenges due to its complex kinematics/dynamics and target object pose acquisition. This paper introduces a fully-actuated AM which consists of a fully-actuated hexarotor and a 3-DoF manipulator. The fully-actuated aerial platform provides a more stable view for the camera during the AM motion. The feedback linearization controller is used in the aerial platform to ensure the stability of the AM during the motion of the manipulator. The YOLO v5 object detector combines the Oriented Bounding Box (OBB) to form a rotating object detector which can identify the target object and obtain its tilt angle. Combined with the depth camera, the position of the target object in three-dimensional (3D) space can be obtained. Within the working space, the manipulator performs autonomous planning and grasping according to the position and tilt angle of the target. Experimental demonstrates the performance of the proposed AM system.

How to cite this publication

Shuang Hao, Guangming Song, Yue Gu, Juzheng Mao, Zichao Ji, Shengyu Xie, Aiguo Song (2023). Vision-based Autonomous Detecting and Grasping Framework for the Fully-actuated Aerial Manipulator. , DOI: https://doi.org/10.1109/robio58561.2023.10354730.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2023

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1109/robio58561.2023.10354730

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access