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# IntelligentUAVPathPlanningSimulationSystemS-Drone<br>
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# IntelligentUAVPathPlanningSimulationSystemS-Drone<br>
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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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### [Video Introduction](https://www.yuque.com/u12074055/kb/qqkaw9)
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## Main Features
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<br>
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<br>
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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.
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### 1. Software Interface
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### 2. Software Architecture (plug-ins to be implemented for some extended functions)
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### 3. Code
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### 4. Multidimensional View
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#### Two-dimensional view (1)
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#### Two-dimensional view (2)
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#### 3d view
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### 5. UAV Control
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#### Console Control
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#### Intelligent Control
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#### Ground Station Control
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### 6. Set Flight Mission
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#### Flight Mission(1)
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#### Flight Mission(2)
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#### Flight Mission(3)
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### 7. Path planning
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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.
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#### Directory Structure<br>
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@ -168,24 +168,24 @@ The path algorithm is based on the redevelopment of Huiming Zhou's open source a
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### Outdoor obstacle avoidance
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#### Custom routes and obstacle areas
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#### rrt_2D Path optimization effect chart
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#### Search_2D Path optimization effect chart
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 <br>
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 <br>
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### Indoor obstacle avoidance
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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:<br>
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#### rrt_3D_Indoor obstacle avoidance renderings
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#### Search_3D_Indoor obstacle avoidance renderings
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### Path optimization
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To optimize the flight paths of multiple UAV clusters, we add random, greedy, path optimal algorithm clustering, regional path random generation, regional path shortest distance first generation algorithm.
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#### The algorithm generates the flight status of each UAV, the navigation point and the flight distance information
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#### Path optimization effect chart
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## Solve The Problem
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@ -201,11 +201,11 @@ The advantage of using this software is that it absorbs the results obtained abr
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### On the formation simulation of multi-UAV
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Using SITL to simulate multi-UAV formation under Windows, please refer to the following article. Note that the path should be tested under ArduCopter/ :<br>
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https://blog.csdn.net/jzhd2015/article/details/108987818<br>
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<br>
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<br>
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Test of two-plane formation path algorithm:<br>
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<br>
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<br>
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It can plan the flight path of left wing and right wing UAV respectively:<br>
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<br>
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<br>
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### About the flight line under Flylitchi
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I happened to see it on the oil pipe. After planning the flight route on the ground station Mission Planner and saving the navigation point, I could edit it with Excel, and then import the modified data in CSV format through the webpage or Android Litchi, so as to realize the DJI UAV flying in accordance with the flight route on the Litchi App.<br>
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@ -222,30 +222,6 @@ Android：Litchi for DJI Mavic / Phantom / Inspire / Spark Version 4.7.0<br>
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### Mission Planner + Google Earth log generates 3D trajectory maps
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Google China satellite map is used instead. It mainly imports the planned path generated by the Mission Planner or the console of the ground station to the map, with.waypoint or KMZ file as the main file.<br>
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Please wait for updates on other extensions....
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## Gratitude<br>
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**CSDN：**<br>
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https://blog.csdn.net/qinguoxiaoziyangyue/article/details/77712064<br>
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https://blog.csdn.net/guojunxiu/article/details/79158843<br>
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https://blog.csdn.net/huihut/article/details/86587782<br>
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https://blog.csdn.net/u010946448/article/details/90718264<br>
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https://blog.csdn.net/jzhd2015/article/details/108987818<br>
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https://blog.csdn.net/jzhd2015/article/details/108663961<br>
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**Zhihu:**<br>
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https://zhuanlan.zhihu.com/p/50900595
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https://zhuanlan.zhihu.com/p/62017292<br>
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**Freesion：**<br>
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https://www.freesion.com/article/2344608320/<br>
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**Gitee：**<br>
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https://gitee.com/wwy2018/XTDrone<br>
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**Github：**<br>
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https://github.com/dhondta/dronesploit<br>
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## Project Link<br>
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JianShu：https://www.jianshu.com/p/b1e6b2efb96f<br>
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Github：https://github.com/wangwei39120157028/IntelligentUAVPathPlanningSimulationSystem-Drone<br>
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Gitee：https://gitee.com/wwy2018/intelligent-uavpath-planning-simulation-system-S<br>
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Welcome To Star！！！
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