UAVS_Drone智能无人机路径规划仿真系统是一个具有操作控制精细、平台整合性强、全方向模型建立与应用自动化特点的软件。它以A、B两国在C区开展无人机战争为背景，该系统的核心功能是通过仿真平台规划无人机航线，并进行验证输出，数据可导入真实无人机，使其按照规定路线精准抵达战场任一位置，支持多人多设备编队联合行动。 UAVS_Drone Intelligent UAV path planning simulation system is a software with fine operation control, strong platform integration, omnidirectional model building and application automation. It takes the UAV war between A and B in Zone C as the background. The core function of the system is to plan the UAV route through the simulation platform and verify the output. The data can be imported into the real UAV to make it accurately arrive at any position in the battlefield according to the specified route and support the joint action of multi-person and multi-device formation.

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视频简介

Video Introduction

安装手册

Installation manual

Main Features

System supported by open source SITL uav simulation platform, through FlightGear rendering real battlefield environment, integrated modeling, 2 d vertical, three-dimensional dynamic model simulation, script control, ground station monitoring, data processing, and other functions, in addition, the simulation system supports a variety of global map load, simulate the key region of the three dimensional environment, can be used throughout the global remote sensing monitoring in the scene.

1. Software Interface

2. Software Architecture (plug-ins to be implemented for some extended functions)

3. Code

4. Multidimensional View

Two-dimensional view (1)

Two-dimensional view (2)

3d view

5. UAV Control

Console Control

Intelligent Control

Ground Station Control

6. Set Flight Mission

Flight Mission(1)

Flight Mission(2)

Flight Mission(3)

7. Path planning

The path algorithm is based on the redevelopment of Huiming Zhou's open source algorithm library (ZHM-Real /PathPlanning), adding elements such as UAV simulation, geographic coordinate conversion, and Leaflet visualization.

Directory Structure

drone_PathPlanning.
	├─fence.txt
	├─leaflet_folium_plot.py
	├─mission.waypoints
	│          
	├─folium-0.12.1
	│              
	├─leaflet
	│          
	├─results
	│      
	├─Sampling_based_Planning
	│  ├─algorithm_mission_rrt2D
	│  │      algorithm_mission_batch_informed_trees.waypoints
	│  │      algorithm_mission_dubins_rrt_star.waypoints
	│  │      algorithm_mission_dynamic_rrt.waypoints
	│  │      algorithm_mission_extended_rrt.waypoints
	│  │      algorithm_mission_fast_marching_trees.waypoints
	│  │      algorithm_mission_informed_rrt_star.waypoints
	│  │      algorithm_mission_rrt.waypoints
	│  │      algorithm_mission_rrt_connect.waypoints
	│  │      algorithm_mission_rrt_star.waypoints
	│  │      algorithm_mission_rrt_star_smart.waypoints
	│  │      
	│  ├─indoor_obstacle_avoidance_rrt3D
	│  │      IOAPath_rrt3D.waypoints
	│  │      IOAPath_rrt_star3D.waypoints
	│  │      IOA_BIT_star3D.waypoints
	│  │      IOA_extend_rrt3D.waypoints
	│  │      
	│  ├─rrt_2D
	│  │      batch_informed_trees.py       BIT*算法
	│  │      draw.py
	│  │      dubins_path.py                Dubins路径算法
	│  │      dubins_rrt_star.py            Dubins_rrt*算法
	│  │      dynamic_rrt.py                动态RRT算法
	│  │      env.py
	│  │      extended_rrt.py               Extended_RRT算法
	│  │      fast_marching_trees.py        FMT*算法
	│  │      informed_rrt_star.py          Informed_rrt*算法
	│  │      judge.py
	│  │      plotting.py
	│  │      queue.py
	│  │      rrt.py                        rrt算法
	│  │      rrt_connect.py                RRT_CONNECT算法
	│  │      rrt_star.py                   rrt*算法
	│  │      rrt_star_smart.py             rrt*-Smart算法
	│  │      utils.py
	│  │      __init__.py
	│  │          
	│  ├─rrt_2D_路径优化效果图
	│  │      
	│  ├─rrt_3D
	│  │     ABIT_star3D.py
	│  │     BIT_star3D.py
	│  │     dynamic_rrt3D.py
	│  │     env3D.py
	│  │     extend_rrt3D.py
	│  │     FMT_star3D.py
	│  │     informed_rrt_star3D.py
	│  │     plot_util3D.py
	│  │     queueL.py
	│  │     rrt3D.py
	│  │     rrt_connect3D.py
	│  │     rrt_star3D.py
	│  │     utils3D.py
	│  │          
	│  └─rrt_3D_室内避障效果图
	│          
	└─Search_based_Planning
		├─algorithm_mission_Search2D
		│      algorithm_mission_Anytime_D_star.waypoints
		│      algorithm_mission_ARAstar.waypoints
		│      algorithm_mission_Astar.waypoints
		│      algorithm_mission_Best_First.waypoints
		│      algorithm_mission_bfs.waypoints
		│      algorithm_mission_Bidirectional_a_star.waypoints
		│      algorithm_mission_Bidirectional_dfs.waypoints
		│      algorithm_mission_Bidirectional_Dijkstra.waypoints
		│      algorithm_mission_Bidirectional_D_star.waypoints
		│      algorithm_mission_Bidirectional_D_star_Lite.waypoints
		│      algorithm_mission_Bidirectional_LPAstar.waypoints
		│      algorithm_mission_Bidirectional_LRTAstar.waypoints
		│      algorithm_mission_Bidirectional_RTAAStar.waypoints
		│      
		├─indoor_obstacle_avoidance_Search_3D
		│      IOA_Anytime_Dstar3D.waypoints
		│      IOA_Astar3D.waypoints
		│      IOA_bidirectional_Astar3D.waypoints
		│      IOA_Dstar3D.waypoints
		│      IOA_DstarLite3D.waypoints
		│      IOA_LP_Astar3D.waypoints
		│      IOA_LRT_Astar3D.waypoints
		│      IOA_RTA_Astar3D.waypoints
		│      
		├─Search_2D
		│     Anytime_D_star.py           AnytimeD*搜索算法
		│     ARAstar.py                  ARA*搜索算法
		│     Astar.py                    A*搜索算法
		│     Best_First.py               最佳路径优先搜索算法
		│     bfs.py                      广度优先算法
		│     Bidirectional_a_star.py     双向A*搜索算法
		│     dfs.py                      深度优先搜索算法
		│     Dijkstra.py                 Dijkstra搜索算法
		│     D_star.py                   D*搜索算法
		│     D_star_Lite.py              D*反向搜索算法
		│     env.py
		│     LPAstar.py                  终身规划A*算法
		│     LRTAstar.py                 LRTA*搜索算法
		│     plotting.py
		│     queueL.py
		│     RTAAStar.py                 RTAA*搜索算法
		│          
		├─Search_2D_路径优化效果图
		│      
		├─Search_3D
		│     Anytime_Dstar3D.py
		│     Astar3D.py
		│     bidirectional_Astar3D.py
		│     Dstar3D.py
		│     DstarLite3D.py
		│     env3D.py
		│     LP_Astar3D.py
		│     LRT_Astar3D.py
		│     plot_util3D.py
		│     queueL.py
		│     RTA_Astar3D.py
		│     utils3D.py
		│          
		└─Search_3D_室内避障效果图

Outdoor obstacle avoidance

Custom routes and obstacle areas

自定义路线与障碍区

rrt_2D Path optimization effect chart

rrt_2D_路径优化效果图

Search_2D Path optimization effect chart

Search_2D_路径优化效果图

Indoor obstacle avoidance

Because the indoor structure has the characteristics of narrow space and many distractions, the path planning degree at this time focuses more on the effect of three-dimensional obstacle avoidance, and the map is meaningless. Based on Huiming Zhou's open source algorithm library, the indoor environment was created using the idea of modeling, and the 3D algorithms of Search_based_Planning and Sampling_based_Planning were used to plan the flight path for obstacle avoidance. The flight demo is as follows: IOA_DstarLite3D

rrt_3D_Indoor obstacle avoidance renderings

rrt_3D_室内避障效果图1

Search_3D_Indoor obstacle avoidance renderings

Search_3D_室内避障效果图1

Path optimization

To optimize the flight paths of multiple UAV clusters, we add random

UAVS

Install / Use

README

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