Abstract
Seeking to give unmanned aerial vehicles (UAVs) a higher level of autonomous control, this study uses edge computing systems to replace the ground control station (GCS) commonly used to control UAVs. Since the GCS belongs to the central control architecture, the edge computing system of the distributed architecture can give drones more flexibility in dealing with changing environmental conditions, allowing them to autonomously and instantly plan their flight path, fly in formation, or even avoid obstacles. Broadcast communications are used to realize UAV-to-UAV communications, thus allocating tasks among a swarm of UAVs and ensuring that each individual UAV collaborates as an integrated member of the group. The dynamic path programming problem for UAV swarm missions uses a two-phase tabu search with a 2-Opt exchange method and an A* search as the path programming algorithm. Distance is taken as a cost function for path programming. The turning points of no-fly zones are then increased and expanded based on drone fleet coverage, thus preventing drones from entering prohibited areas. Unlike previous work, which mostly considers only single no-fly zones, this approach accounts for multiple restricted areas, ensuring that a UAV swarm can complete its assigned task without violating no-fly zones. A drone encountering an obstacle while traveling along the route set by the algorithm will update the map information in real time, allowing for instant recharting of the optimal path to the goal as a reverse search using the D* Lite algorithm.
Highlights
Unmanned aerial vehicles (UAVs) are a type of unmanned aircraft system that is remote controlled from a ground station
Each drone operates as an edge computing device
This study improves existing path planning algorithms and incorporates the constudyrestricted improves existing path algorithms and incorpor ditionsThis of multiple navigation zones and planning formation flying as considerations for restricted navigation zone avoidance during pathzones planning
Summary
Unmanned aerial vehicles (UAVs) are a type of unmanned aircraft system that is remote controlled from a ground station. UAVs were initially used mainly by militaries to conduct “dull, dirty, or dangerous” missions [1], including reconnaissance or air-tosurface ordinance strikes. Complicated missions in uncertain environments frequently call for the use of UAV swarms, which distribute tasks to individual drones, with applications including formation flight, inspired by the formation flight behavior of birds. In 2015, the United States Air. Force (USAF) proposed the “loyal wingmen” concept [2], in which support drones help the leader engage in reconnaissance or airstrikes and protect the leader from attack. Force (USAF) proposed the “loyal wingmen” concept [2], in which support drones help the leader engage in reconnaissance or airstrikes and protect the leader from attack This technique reflects the application value of UAV swarms. Other swarm applications could allow different drones to carry different sensing devices or additional sensors to enhance mission flexibility and robustness in the face of uncertain and changing environmental conditions [3,4]
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