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Target seeking behaviour of an intelligent mobile robot using advanced particle swarm optimization

机译:使用高级粒子群算法的智能移动机器人的目标寻找行为

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The present research work aims to develop two different motion planners for an autonomous mobile robot. The developed motion planners are inspired by particle swarm optimization and are useful for generating feasible paths by the robot within its unknown environment. Each motion planner works on its own fitness function and each fitness function are modelled based on the robot sensory information. Path analysis results showed that both motion planners are generating collision free paths and reaches its destination within its workspace. Finally, comparison has been done in between the developed PSO based motion planners.
机译:本研究工作旨在为自主移动机器人开发两种不同的运动计划器。研发的运动计划器受到粒子群优化的启发,对于在未知环境中由机器人生成可行路径很有用。每个运动计划者都在自己的适应功能上工作,并且每个适应功能都基于机器人的感官信息进行建模。路径分析结果表明,两个运动计划器都在生成无碰撞的路径并到达其工作空间内的目的地。最后,在已开发的基于PSO的运​​动计划器之间进行了比较。

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