Design of Multi-Objective Path Planning for UAV Based on Adaptive Optimization

This paper proposes a multi-objective path planning method for UAVs based on adaptive optimization, aiming to improve the path planning efficiency and accuracy of UAVs in complex environments. This method uses an adaptive optimization algorithm to achieve dynamic adjustment of path planning parameters, so that it can more properly handle environmental uncertainties and multi-objective constraints. A mathematical model for multi-objective path planning of UAVs is constructed, important objectives such as flight time, path length, and energy consumption are defined, and an adaptive optimization algorithm is designed. The algorithm allows the UAV to autonomously select the optimal path by adjusting the search step size and weight distribution in real time. Secondly, the effectiveness of the designed algorithm is confirmed by multiple simulation experiments. The simulation experiment results show that compared with traditional optimization methods, this algorithm shows extremely obvious advantages in shortening path length and reducing energy consumption. The path length is reduced by an average of 15% and energy consumption is reduced by about 20%. The method proposed in this paper provides an operational solution for autonomous path planning of UAVs in dynamic and multi-objective environments.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/icftic64248.2024.10913457
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50
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article

Design of Multi-Objective Path Planning for UAV Based on Adaptive Optimization

R.C. Luo
2 citations
Robotic Path Planning Algorithms
0.50
article

Design of Multi-Objective Path Planning for UAV Based on Adaptive Optimization

R.C. Luo
article en
2 citations

Abstract

This paper proposes a multi-objective path planning method for UAVs based on adaptive optimization, aiming to improve the path planning efficiency and accuracy of UAVs in complex environments. This method uses an adaptive optimization algorithm to achieve dynamic adjustment of path planning parameters, so that it can more properly handle environmental uncertainties and multi-objective constraints. A mathematical model for multi-objective path planning of UAVs is constructed, important objectives such as flight time, path length, and energy consumption are defined, and an adaptive optimization algorithm is designed. The algorithm allows the UAV to autonomously select the optimal path by adjusting the search step size and weight distribution in real time. Secondly, the effectiveness of the designed algorithm is confirmed by multiple simulation experiments. The simulation experiment results show that compared with traditional optimization methods, this algorithm shows extremely obvious advantages in shortening path length and reducing energy consumption. The path length is reduced by an average of 15% and energy consumption is reduced by about 20%. The method proposed in this paper provides an operational solution for autonomous path planning of UAVs in dynamic and multi-objective environments.

Shandong University of Technology (CN)
Openalex Percentile: Top 32%
Robotic Path Planning Algorithms
0.50
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