In current trends, Unmanned Aerial vehicles adopt a wide range of services for several applications, such as logistics, rescue operations, and real-time monitoring. UAVs’ are proven be provide a safe and cost-effective solution. Efficient Path planning is crucial to the navigation of UAVs in different environments. However, finding an optimal path is challenging as it is about more than just finding the shortest path but also considering many factors, such as path generation time and path quality. The present work aims to design and develop an efficient algorithm for providing an obstacle-free path approach between two points. The present work proposed a novel path planning scheme (Rapid A*) using a bounded line-of-sight approach to provide a guaranteed solution and achieve motivating results concerning path length and path generation time. We also provide a detailed comparative analysis of the proposed RA* approach with trademark and the latest approaches A*, Beam Search, IDA*, DWA*, and Theta* algorithm. In terms of path generation time and while considering the realistic path, the proposed approach outperforms other approaches and achieves approx 18% less path generation time as compared to A*, Beam Search and Theta* algorithm and 4% less path length as compared to A*, Beam Search, IDA* and DWA* algorithm.

在当前趋势下，无人机在物流、救援行动和实时监控等多种应用中采用了广泛的服务。事实证明，无人机可以提供安全且经济高效的解决方案。高效的路径规划对于无人机在不同环境下的导航至关重要。然而，寻找最优路径具有挑战性，因为它不仅仅是寻找最短路径，还需要考虑许多因素，例如路径生成时间和路径质量。目前的工作旨在设计和开发一种有效的算法，用于提供两点之间的无障碍路径方法。目前的工作提出了一种新颖的路径规划方案（Rapid A*），使用有界视线方法来提供有保证的解决方案并实现有关路径长度和路径生成时间的激励结果。我们还对提出的带有商标的 RA* 方法和最新方法 A*、Beam Search、IDA*、DWA* 和 Theta* 算法进行了详细的比较分析。在路径生成时间方面，在考虑实际路径的同时，所提出的方法优于其他方法，与 A*、Beam Search 和 Theta* 算法相比，路径生成时间减少约 18%，与 A 相比，路径长度减少 4% *、波束搜索、IDA* 和 DWA* 算法。