Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning

Roberge, Vincent; Tarbouchi, Mohammed; Labonté, Gilles

doi:10.1109/tii.2012.2198665

Cited by 862 publications

(388 citation statements)

References 15 publications

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“…Interior point algorithm (IPA) is used [9] in order to tolerate the mismatch, but IPA has a poor robustness and convergence performance. Particle swarm optimization (PSO) algorithm is a kind of swarm intelligent algorithm [10,11] and widely used in optimal network [12], resources scheduling [13], signal design [14], route planning [15,16], et al, its robustness and convergence performance is much better than IPA. Hence we use PSO algorithm and the concept of equivalent multi-SIMO radars to modify the beamforming and reduce the computation of solving…”

Section: B Pso-mvdr Based On Equivalent Multi-simo Radars With Mismamentioning

confidence: 99%

Dimension-reduced Robust Beamforming Method for MIMO Radar

Li¹,

Jiang²,

Dan³

et al. 2013

Proceedings of the 3rd International Conference on Electric and Electronics

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Abstract-A new robust beamforming algorithm for multiple-input and multiple-output (MIMO) radar is proposed in the presence of unknown mismatches phenomenon of the desired signal steering vector. Considering that the transmitted waveforms of MIMO radar are orthogonal to each other, after matched filtering MIMO radar can be thought equivalent to multiple single input and multiple output (multi-SIMO) radars. So we decomposed the full-dimensional beamforming of MIMO radar into multiple dimension-reduced beamforming for equivalent multi-SIMO radars. This kind of equivalent has benefits of reducing the number of whole sampling data and the dimensions of sampling data that each equivalent SIMO radar needs to process. Otherwise, we used particle swarm optimization (PSO) algorithm to modify the mismatch of each desired signal steering vector, and the robustness has been greatly improved because the use of PSO. Numerical experiments with the desired signal steering vector mismatches are provided to demonstrate the effectiveness of the proposed dimension-reduced robust adaptive beamforming algorithm.

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Section: B Pso-mvdr Based On Equivalent Multi-simo Radars With Mismamentioning

confidence: 99%

Dimension-reduced Robust Beamforming Method for MIMO Radar

Li¹,

Jiang²,

Dan³

et al. 2013

Proceedings of the 3rd International Conference on Electric and Electronics

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“…A multiobjective genetic algorithm (GA) was used by Liu and Huang [5] to search the optimal motion trajectory, though the stability of the base attitude control can be achieved, the multiobjective GA is more complex to realize. The GA and the particle swarm optimization (PSO) algorithm, gravitational search algorithm (GSA) and PSO algorithm, and immune PSO algorithm for trajectory planning were, respectively, presented by Roberge et al [6], Constantin and Lucian [7], and Wang and Yu [8], because the structure of the manipulator with 7 degrees of freedom (7-DOF) is different from those mentioned in the above literature, and the methods are difficult to control the manipulator presented in this paper. So the paper combines PSO algorithm with simulated annealing algorithm to minimize the base attitude disturbance through planning the joint trajectory.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning of 7-DOF Space Manipulator for Minimizing Base Disturbance

Zhang

Wang

Zhou

2016

International Journal of Advanced Robotic Systems

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In the free-floating mode, there is intense dynamic coupling existing between the space manipulator and the base, and the base attitude may change while performing a motion with its manipulator. Therefore, it is necessary to reduce the interference that resulted from the manipulator movement. For planning trajectories of the space manipulator with 7 degrees of freedom (7-DOF), simulated annealing particle swarm optimization (SAPSO) algorithm is presented in the paper. Firstly, kinematics equations are setup. Secondly, the joint functions are parameterized by sinusoidal functions, and the objective function is defined according to the motion constraints of manipulator and accuracy requirements of the base attitude. Finally, SAPSO algorithm is used to search the optimal trajectory. The simulation results verify the proposed method.

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“…It could find closer sub-optimal paths with high certainty for all the tested networks [9]. Vincent used the genetic algorithm (GA) and the particle swarm optimization algorithm (PSO) to cope with the complexity of the problem and compute feasible and quasi-optimal trajectories in a complex 3D environment by using a parallel implementation [10]. Fu presented a hybrid differential evolution (DE) with quantum-behaved particle swarm optimization (QPSO) for the unmanned aerial vehicle route planning,which combined the DE algorithm with the QPSO algorithm in an attempt to further enhance the performance of both algorithms [11].…”

Section: Introductionmentioning

confidence: 99%

Research on Path Optimization with PSO for Unmanned Vehicle

Jia

Lei

2015

Int. J. Onl. Eng.

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Abstract-The development of autonomous unmanned vehicles is of high interest to many organizations around the world and path planning is the key point of the navigation for the autonomous unmanned vehicle. Intelligent algorithms have been applied in this field and an essential aspect of unmanned vehicles autonomy is the ability for automatic path planning. In this paper, particle swarm optimization algorithm as one of new swarm intelligent optimization methods is introduced into a path planning for autonomous vehicle, which is constructed of a particle representation methods for vehicle routing problem with fast convergence speed. The results show that the particle swarm optimization algorithm can obtain the solution of the vehicle routing problem quickly and effectively. It is a good method for solving the vehicle routing problem.

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Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning

Cited by 862 publications

References 15 publications

Dimension-reduced Robust Beamforming Method for MIMO Radar

Dimension-reduced Robust Beamforming Method for MIMO Radar

Trajectory Planning of 7-DOF Space Manipulator for Minimizing Base Disturbance

Research on Path Optimization with PSO for Unmanned Vehicle

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