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Local exploration strategies for a mobile robot in a highly dynamic environment

机译:高动态环境中移动机器人的本地探索策略

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In this paper, three strategies for navigation in highly dynamic environments are developed and their exploration effectiveness compared. These strategies include a collision avoidance strategy, a random wandering strategy and a goal planning strategy. Existing exploration and surveillance techniques make extensive use of metric maps for localisation and navigation which can be of little use in an environment that has many moving obstacles. While the strategies compared here are not specifically designed for exploration, they allow navigation without the need to store and maintain a map. The evenness or positional distribution over time as well as the speed of exploration are taken as measures of exploration efficacy and applicability to surveillance. The comparison of the strategies shows that the goal planning strategy performs far better than the other two, warranting a significant increase in the complexity and thus computational resources required for successful implementation onto physical platforms.
机译:在本文中,开发了三种在高动态环境中导航的策略,并比较了它们的探索效果。这些策略包括避免碰撞策略,随机游荡策略和目标计划策略。现有的探索和监视技术广泛使用了公制地图进行定位和导航,而在有许多移动障碍的环境中,这种地图很少使用。尽管此处比较的策略并非专门为探索而设计,但它们可以导航而无需存储和维护地图。随时间推移的均匀性或位置分布以及探测的速度被用作探测效力和监视适用性的度量。这些策略的比较表明,目标计划策略的性能远优于其他两个策略,从而确保了复杂性的显着提高,从而大大提高了成功实施到物理平台所需的计算资源。

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