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A faster path planner using accelerated particle swarm optimization

机译:使用加速粒子群优化的更快的路径规划器

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摘要

The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.
机译:放置小型移动机器人在大型建筑物中移动以检测潜在入侵者的想法已经存在了一段时间。但是,仍然有两个主要障碍需要克服:将自己定位在环境中并决定如何以合理的计算成本安全有效地移动。本文描述了一种数学模型,该模型用于开发使用可视化同时定位和映射以及加速粒子群智能路径规划器的自主式低成本移动机器人系统的方案。结果表明,该系统可以为室内移动机器人导航问题提供解决方案。计算机技术的进步使该技术成为未来家庭服务机器人的一种经济高效的解决方案。

著录项

  • 来源
    《Artificial life and robotics》 |2012年第2期|233-240|共8页
  • 作者单位

    Faculty of Engineering and Built Environment, School of Materials and Mechanical Engineering, National University of Malaysia (UKM), 43600 Bangi, Malaysia, Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia;

    Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia;

    Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia;

    Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    artificial intelligence; global path planning; local path planning; SLAM; swarm robotics;

    机译:人工智能;全球路径规划;当地路径规划;SLAM;群机器人;

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