Author ORCID Identifier
Document Type
Conference Paper
Disciplines
Computer Sciences
Abstract
Autonomous delivery-by-drone of packages is an active area of research and commercial development. However, the assessment of safe dropping/ delivery zones has received limited attention. Ensuring that the dropping zone is a safe area for dropping, and continues to stay safe during the dropping process is key to safe delivery. This paper proposes a simple and fast classifier to assess the safety of a designated dropping zone before and during the dropping operation, using a single onboard camera. This classifier is, as far as we can tell, the first to address the problem of safety assessment at the point of deliveryby- drone. Experimental results on recorded drone videos show that the proposed classifier provides both average precision and average recall of 97% in our test scenarios.
DOI
https://doi.org/10.1109/IPAS55744.2022.10052868
Recommended Citation
A. Alsawy, A. Hicks, D. Moss and S. Mckeever, "An Image Processing Based Classifier to Support Safe Dropping for Delivery-by-Drone," 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS), Genova, Italy, 2022, pp. 1-5, doi: 10.1109/IPAS55744.2022.10052868
Funder
the European Union’s Horizon 2020 Research and innovation
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Details
2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS)
https://doi.org/10.1109/IPAS55744.2022.10052868