Parallel Evolutionary Algorithms for Uav Path Planning
نویسندگان
چکیده
Evolutionary computation (EC) techniques have been successfully applied to compute near-optimal paths for unmanned aerial vehicles (UAVs). Premature convergence prevents evolutionary-based algorithms from reaching global optimal solutions. This often leads to unsatisfactory routes that are suboptimal to optimal path planning problems. To overcome this problem, this paper presents a framework of parallel evolutionary algorithms for UAV path planning, in which several populations evolve simultaneously and compete with each other. The parallel evolution technique provides more exploration capability to planners and significantly reduces the probability that planners are trapped in local optimal solutions.
منابع مشابه
UAV Swarm Mission Planning Development Using Evolutionary Algorithms and Parallel Simulation - Part II SCP-195
The purpose of this paper is to discuss the design and implementation of comprehensive mission planning systems for swarms of autonomous aerial vehicles (UAV). Such a system could integrate several problem domains including path planning, vehicle routing, and swarm behavior as based upon a hierarchical architecture. The example developed system consists of a parallel multi-objective evolutionar...
متن کاملStudy of Evolutionary and Swarm Intelligent Techniques for Soccer Robot Path Planning
Finding an optimal path for a robot in a soccer field involves different parameters such as the positions of the robot, positions of the obstacles, etc. Due to simplicity and smoothness of Ferguson Spline, it has been employed for path planning between arbitrary points on the field in many research teams. In order to optimize the parameters of Ferguson Spline some evolutionary or intelligent al...
متن کاملUAV Dynamic Path Planning for Intercepting of a Moving Target: A Review
An Unmanned Aerial Vehicle (UAV) has to possess three abilities to function autonomously. The three abilities are localization, mapping and path planning. Path planning guides the UAV to find a feasible path, meaning a path that meets safety, kinematic and optimization constrains. In order to intercept a moving target, dynamic path planning must be used due to target movement. To produce a feas...
متن کاملParameter Selection for Biogeography-based Optimization in Unmanned Aerial Vehicle Path Planning
Biogeography-based optimization (BBO) has recently become popular in unmanned aerial vehicle (UAV) path planning. Similar to other evolutionary algorithms, the performance of BBO is affected when the parameter setting is not finely tuned. Therefore, the BBO parameters are optimized in this research particularly for application in UAV path planning. Each combination setting of parameters is simu...
متن کاملA Synthesizable Hardware Evolutionary Algorithm Design for Unmanned Aerial System Real-Time Path Planning
The main objective of this paper is to detail the development of a feasible hardware design based on Evolutionary Algorithms (EAs) to determine flight path planning for Unmanned Aerial Vehicles (UAVs) navigating terrain with obstacle boundaries. The design architecture includes the hardware implementation of Light Detection And Ranging (LiDAR) terrain and EA population memories within the hardw...
متن کامل