As an effective path exploration technology, dung Beetle algorithm has been widely used in the path planning of unmanned aerial vehicle autonomous navigation. In this paper, a 3D path planning strategy for unmanned aerial vehicles (UAS) is proposed by optimizing the dung beetle algorithm, aiming to overcome the challenges of local optimal traps, redundant turning points and low convergence efficiency encountered by traditional intelligent bionic algorithms when dealing with complex spatial path planning of UAS. First, based on mathematical modeling technology, we built a three-dimensional simulation environment of mountain terrain, and precisely set the objective function and constraint conditions of the UAV to ensure the authenticity and practicability of the experiment scene. We innovatively introduced Fuch and Logistic chaotic mapping mechanisms to optimize the initial population allocation of the dung beetle algorithm, which significantly enhanced the global exploration capability of the algorithm. At the same time, we designed an adaptive nonlinear decline strategy to dynamically regulate the number of dung beetles in different stages of the algorithm, thus accelerating the convergence process of the algorithm. In addition, in order to achieve smooth transition of the path, we use Bessel curve technology to perform fine processing on the generated path.
Three-Dimensional Path Planning of Unmanned Aerial Vehicle Based on Hybrid Strategy and Improved Dung Beetle Optimization Algorithm
15.11.2024
1742448 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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