A New Particle Swarm Optimization Method for the Path Planning of UAV in 3D Environment PEHLIVANOGLU
نویسنده
چکیده
Particle swarm optimization (PSO) method is relatively a new population-based intelligence algorithm and exhibits good performance in optimization problems. However, during the optimization process, the particles become more and more similar, and gather into the neighborhood of the best particle in the swarm, which makes the swarm prematurely converged possibly around the local solution. PSO technique can be augmented with an additional mutation operator that provides diversity and helps prevent premature convergence on local optima. In this paper, mathematical analysis of a basic PSO is reissued and a diversity concept is evaluated in commonly used PSO algorithms including constriction factor PSO, inertial weight PSO, Gaussian mutation PSO, and a new vibrational mutation PSO combining the idea of mutation strategy related to periodicity. New algorithm is tested and compared with selected PSO algorithms. The comparative experiments have been conducted on a wide range of nonlinear functions and a path planning problem of unmanned aerial vehicle (UAV) in three-dimensional (3D) terrain environment. The results give insight into how mutation operator effects the nature of the diversity and show that the addition of a mutation operator with a periodicity concept can significantly enhance the optimization performance.
منابع مشابه
Online Path Planning for UAV Using an Improved Differential Evolution Algorithm
This paper presents a 3D online path planning algorithm for unmanned aerial vehicle (UAV) flying in partially known hostile environment. In order to provide a smooth fight route for UAV, the algorithm adopts B-Spline curve to describe UAV’s path whose control points are optimized by an improved differential evolution algorithm. The planner gradually produces a smooth path for UAV from starting ...
متن کاملPSO-Based Path Planning Algorithm for Humanoid Robots Considering Safety
In this paper we introduce an improvement in the path planning algorithm for the humanoid soccer playing robot which uses Ferguson splines and PSO (Particle Swarm Optimization). The objective of the algorithm is to find a path through other playing robots to the ball, which should be as short as possible and also safe enough. Ferguson splines create preliminary paths using random generated para...
متن کاملReal-time Path Planning Strategy for UAV Based on Improved Particle Swarm Optimization
Unmanned Aerial Vehicle (UAV) path planning is divided into off-line static path planning and real-time dynamic path planning. The former one is applied to the ideal situation that the terrain has been clear, and there is no unexpected situation in flight. Actually, however, the flight situation is very complex, we have to adopt real-time path planning based on off-line static path planning. To...
متن کاملSolving Economic Dispatch in Competitive Power Market Using Improved Particle Swarm Optimization Algorithm
Generally the generation units in the traditional structure of the electricity industry try to minimize their costs. However, in a deregulated environment, generation units are looking to maximize their profits in a competitive power market. Optimum generation planning in such structure is urgent. This paper presents a new method of solving economic dispatch in the competitive electricity marke...
متن کاملDrone Path Planning
Unmanned Aerial Vehicles (UAV) become more and more popular today. The chairman of DJI which is one of the most important UAV producers told an online magazine that their turnover increased by a factor of four in the last years [1]. This development validates the increasing popularity of UAVs. But it is still challenging to control them and it is even more challenging to film important surface ...
متن کامل