Effective path planning is a pivotal challenge across various domains, from robotics to logistics and beyond. This research is centred on the development and evaluation of the Dynamic Curvature-Constrained Path Planning Algorithm (DCCPPA) within two dimensional space. DCCPPA is designed to navigate constrained environments, optimising path solutions while accommodating curvature constraints.The study goes beyond algorithm development and conducts a comparative analysis with two established path planning methodologies: Rapidly Exploring Random Trees (RRT) and Probabilistic Roadmaps (PRM). These comparisons provide insights into the performance and adaptability of path planning algorithms across a range of applications.This research underscores the versatility of DCCPPA as a path planning algorithm tailored for 2D space, demonstrating its potential for addressing real-world path planning challenges across various domains. Index Terms Path Planning, PRM, RRT, Optimal Path, 2D Path Planning.

翻译：有效的路径规划是从机器人学到物流等众多领域面临的关键挑战。本研究聚焦于二维空间中动态曲率约束路径规划算法（DCCPPA）的开发与评估。DCCPPA旨在在受限环境中进行导航，在满足曲率约束的同时优化路径解。本研究不仅开发了算法，还与两种成熟的路径规划方法——快速扩展随机树（RRT）和概率路线图（PRM）——进行了比较分析。这些比较揭示了路径规划算法在各类应用中的性能与适应性。本研究强调了DCCPPA作为一种专为二维空间设计的路径规划算法的通用性，展示了其解决跨领域实际路径规划挑战的潜力。索引词 路径规划，PRM，RRT，最优路径，二维路径规划。