A novel dynamic path planning and obstacle collision detection framework for dynamic UAV networks

Path planning is one of the major issues in real-time UAV communication networks. As the size of the obstacles is increasing in the network, it is difficult to find and construct the new paths due to high computational time and memory. Most of the conventional UAV path planning approaches are static...

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Bibliographic Details
Main Authors: Rao, Durvasula V. Subba, Premi, M. S. Godwin
Format: Conference Proceeding
Language:English
Subjects:
Collision dynamics
Communication networks
Computing time
Obstacle avoidance
Optimization
Path planning
Unmanned aerial vehicles
Online Access:Get full text
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Summary:Path planning is one of the major issues in real-time UAV communication networks. As the size of the obstacles is increasing in the network, it is difficult to find and construct the new paths due to high computational time and memory. Most of the conventional UAV path planning approaches are static in nature and support limited obstacles in the communication network. Also, most of these models detect fixed sized obstacles in the specified locations or regions. In this paper, an advanced dynamic path planning model is implemented on multi-level obstacle collision detection. In this model, an optimization functions are defined to each UAV node in order to detect the arbitrary obstacles in the network. Experimental results proved that the present multiple obstacle detection model is better than the conventional static UAV path planning models in terms of accuracy, run time (ms) are concerned.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0162131