scholarly journals Real-Time Swarm Search Method for Real-World Quadcopter Drones

2018 ◽  
Vol 8 (7) ◽  
pp. 1169 ◽  
Author(s):  
Ki-Baek Lee ◽  
Young-Joo Kim ◽  
Young-Dae Hong
Keyword(s):  
Real Time ◽  
Optimization Algorithm ◽  
Real World ◽  
Particle Swarm Optimization Algorithm ◽  
Search Method ◽  
Air Pollutant ◽  
Function Optimization ◽  
Benchmark Function ◽  
World Environment ◽  
Repeated Test

This paper proposes a novel search method for a swarm of quadcopter drones. In the proposed method, inspired by the phenomena of swarms in nature, drones effectively look for the search target by investigating the evidence from the surroundings and communicating with each other. The position update mechanism is implemented using the particle swarm optimization algorithm as the swarm intelligence (a well-known swarm-based optimization algorithm), as well as a dynamic model for the drones to take the real-world environment into account. In addition, the mechanism is processed in real-time along with the movements of the drones. The effectiveness of the proposed method was verified through repeated test simulations, including a benchmark function optimization and air pollutant search problems. The results show that the proposed method is highly practical, accurate, and robust.

Improved Particle Swarm Optimization Algorithm and its Application Based on the Aggregation Degree

2013 ◽  
Vol 427-429 ◽  
pp. 1934-1938
Author(s):  
Zhong Rong Zhang ◽  
Jin Peng Liu ◽  
Ke De Fei ◽  
Zhao Shan Niu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Population Diversity ◽  
Function Optimization ◽  
Local Optimum ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

The aim is to improve the convergence of the algorithm, and increase the population diversity. Adaptively particles of groups fallen into local optimum is adjusted in order to realize global optimal. by judging groups spatial location of concentration and fitness variance. At the same time, the global factors are adjusted dynamically with the action of the current particle fitness. Four typical function optimization problems are drawn into simulation experiment. The results show that the improved particle swarm optimization algorithm is convergent, robust and accurate.

scholarly journals Wall-E Surveyor Robot using Wireless Networks

2015 ◽  
Vol 4 (2) ◽  
pp. 143
Author(s):  
Aatish Chandak ◽  
Arjun Aravind ◽  
Nithin Kamath
Keyword(s):  
Wireless Networks ◽  
Real Time ◽  
Real World ◽  
Autonomous Navigation ◽  
Remote Access ◽  
Outdoor Environment ◽  
Ultrasonic Sensors ◽  
Moving Obstacles ◽  
Area Of Interest ◽  
World Environment

The methods for autonomous navigation of a robot in a real world environment is an area of interest for current researchers. Although there have been a variety of models developed, there are problems with regards to the integration of sensors for navigation in an outdoor environment like moving obstacles, sensor and component accuracy. This paper details an attempt to develop an autonomous robot prototype using only ultrasonic sensors for sensing the environment and GPS/ GSM and a digital compass for position and localization. An algorithm for the navigation based on reactive behaviour is presented. Once the robot has navigated to its final location based on remote access by the owner, it surveys the geographical region and uploads the real time images to the owner using an API that is developed for the Raspberry PI’s kernel.

Optimization Design of Gear Train Based on Particle Swarm Optimization Algorithm

2013 ◽  
Vol 373-375 ◽  
pp. 1072-1075 ◽  
Author(s):  
Chang Wei Wu ◽  
Yong Hai Wu ◽  
Cong Bin Ma ◽  
Cheng Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Optimization Design ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Function Optimization ◽  
Gear Train ◽  
Multidimensional Space ◽  
Swarm Optimization ◽  
Tooth Width

Particle swarm optimization algorithms have lots of advantages such as fast convergence speed, good quality of solution and robustness in multidimensional space function optimization and dynamic target optimization. It is suitable for structural optimization design. In this paper, manual transmission gear train of a tractor is taken as research object, the minimum quality and minimum center distance of the gear train is taken as optimization goal, the gear ratio, modulus, helix angle, tooth width and equilibrium conditions of the axial force are taken as the constraints, a multi-objective optimization model of the gear train is established. The optimal structure design programs and Pareto optimal solution are obtained by using particle swarm optimization algorithm.

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