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群体智能算法在无人机路径规划中的应用
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Abstract:
随着无人机技术的快速发展，路径规划作为其核心技术，面临着复杂多变飞行环境和多样化任务需求的挑战。然而，传统路径规划算法在特定场景下虽表现出色，但计算量大、规划时间长且难以适应动态变化，限制了无人机的广泛应用。针对此，群体智能算法凭借其全局搜索能力强、鲁棒性好、易于并行化及广泛适用性，成为无人机路径规划领域的研究热点。本文主要探讨了几种典型的群体智能算法在无人机路径规划中的应用，并对无人机路径规划的未来研究方向进行展望。
With the rapid development of drone technology, path planning, as its core technology, faces the challenges of complex and variable flight environments and diverse task requirements. However, traditional path planning algorithms, although performing well in specific scenarios, have high computational complexity, long planning time, and difficulty in adapting to dynamic changes, limiting the widespread application of drones. In response to this, swarm intelligence algorithms, which are characterized by their strong global search ability, good robustness, easy parallelization, and wide applicability, have become a research hotspot in the field of drone path planning. This paper mainly explores the application of several typical swarm intelligence algorithms in drone path planning and looks forward to the future research directions of drone path planning.
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