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Particle Swarm Optimization Algorithm for finding the brightest spot in an arena

机译:用于在竞技场中找到最亮点的粒子群优化算法

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Particle Swarm Optimization (PSO) algorithm is widely used in Robotic search applications. This paper proposes a PSO algorithm to locate the brightest spot in a given search space using a swarm of robots. Each robot of the swarm acts as a particle in PSO; each particle updates its position, velocity, personal best location and personal best cost measurement based on the light intensity at any position till it reaches its target. The robots communicate the measured light intensity and its position with each other. The position of robots is obtained using ArUco markers with the help of an overhead camera. An ultrasonic sensor is interfaced with the robots for static and dynamic obstacle avoidance. Simulation of the PSO algorithm is implemented using MATLAB software.
机译:粒子群优化(PSO)算法广泛用于机器人搜索应用。本文提出了一种PSO算法,可以使用一群机器人定位给定的搜索空间中最明亮的位置。群体的每个机器人都作为PSO中的粒子;每个粒子根据任何位置的光强度更新其位置,速度,个人最佳位置和个人最佳成本测量,直到它到达其目标。机器人将测量的光强度及其位置彼此传达。使用Aruco标记获得机器人的位置,借助架空相机。超声波传感器与机器人接口,用于静态和动态障碍物避免。使用MATLAB软件实现PSO算法的仿真。

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