Robust Transport and Assembly Automation System Using Vision-Based Control Using UAV

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We propose an automated system that moves blocks to a specific location, such as a block map, using Unmanned Aerial Vehicle (UAV). The system was developed in a simulation environment using Gazebo simulator, and the test environment was set with different GPS noise and illuminance in order to resemble the real environment. To increase the accuracy of the system, we used an algorithm that picks up and places blocks using vision-based controls using deep learning-based object detection and recognition, not just GPS based control. In addition, when picking up and placing blocks, it is easy to execute by using a magnet module rather than a typical manipulator. Our proposed system in simulation experiments in various environments consistently showed excellent performance. The system seems to have robust performance in a more difficult environment than existing robots and has simplicity and efficiency in execution. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Publisher
Springer Science and Business Media Deutschland GmbH
Issue Date
2021-12
Language
English
Citation

8th International Conference on Robot Intelligence Technology and Applications, RiTA 2020, pp.32 - 38

ISSN
2195-4356
DOI
10.1007/978-981-16-4803-8_4
URI
http://hdl.handle.net/10203/288756
Appears in Collection
RIMS Conference Papers
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