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A sub goal seeking approach for reactive navigation in complex unknown environments

机译:在复杂未知环境中进行反应式导航的子目标寻找方法

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Reactive-based approaches are widely used in autonomous navigation. However, in complex unknown environments, pure reactive-based navigation still poses a few challenges since it can be easily trapped by a local minimum and may produce some extra manoeuvres. This paper presents the design of a reactive-based approach for navigation in complex and unknown environments called sub goal seeking, in which depth point maps of the environment are analysed to extract free spaces around the robot. These spaces are then evaluated the one that is most likely to lead to the final goal is chosen as a sub goal. The robot then drives towards these sub goals, instead of the final goal until it is visible. By analysing the environmental structure, dead-ends within robot sensory range are able to be detected thus reducing the chance of being trapped and also reducing unnecessary manoeuvres. This paper also evaluates the performance of the sub goal seeking approach using three criteria, goal achievable ability, safety and maneuvering through extensive simulation and real mobile robot experiments.
机译:基于反应的方法广泛用于自主导航。但是,在复杂的未知环境中,基于纯反应性的导航仍然会遇到一些挑战,因为它很容易被局部最小值所困,并且可能会产生一些额外的动作。本文提出了一种基于反应的方法,用于在复杂和未知环境中导航,该方法称为子目标搜索,该方法分析了环境的深度点图,以提取机器人周围的自由空间。然后评估这些空间,选择最有可能导致最终目标的空间作为子目标。然后,机器人将驶向这些子目标,而不是最终目标,直到可见为止。通过分析环境结构,可以检测机器人感觉范围内的死角,从而减少了被困的机会,并减少了不必要的操作。本文还通过广泛的仿真和真实的移动机器人实验,使用三个标准(可达到目标的能力,安全性和机动性)来评估次目标搜索方法的性能。

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