Journal
IMPROVE: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON IMAGE PROCESSING AND VISION ENGINEERING
Volume -, Issue -, Pages 202-210Publisher
SCITEPRESS
DOI: 10.5220/0011089900003209
Keywords
Image Segmentation; Road Extraction; Weighted Path Planning; A Star; Algorithm; UAV; SAR
Categories
Funding
- Stipendium Hungaricum scholarship
- China Scholarship Council
- Hungarian Ministry of Innovation and Technology
- National Research, Development and Innovation Office
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This study presents a technique for using drones to intelligently plan routes in wilderness environments, utilizing image segmentation and road extraction techniques, as well as the A-star algorithm to calculate optimal routes for people in the field in real-time.
With the development of science and technology, UAVs are increasingly being used and serving humans, especially in the wilderness environment, due to their portability and the ease with which they can reach places that are beyond human reach. In this paper, we present a technique for drones to help humans intelligently plan routes in a field environment. Our approach is firstly based on road extraction techniques in the field of image segmentation, using state-of-the-art D-LinkNet to extract roads from images captured by real-time UAVs. Secondly, the extracted road information is analyzed, the set of main roads and that of the secondary road are distinguished according to the width and the real-time road conditions on the ground, and different weights are assigned to them. Finally, the A star algorithm is used to calculate a route plan with weights based on the human-defined starting and ending points to obtain the optimal route. The results of our task are the simulations on publicly available datasets to show that the method works well to provide the optimal intelligent routes in real-time for people in the field.
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