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Shark-Inspired Target Approach Strategy for Foraging with Visual Clues

机译:鲨鱼启发目标探讨视觉线索的目标方法策略

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Searching is one of the key activities to fulfill any foraging task. When working with robots, most searching strategies depend on image processing, which is one of the most time-consuming processes. In this work, white shark hunting behaviors inspired the proposed strategy for a team of foraging robots to search and approach the objects. Based on current perceptions, a robot can speed up the foraging process by switching between its sensors to approach its target, that is, by depending less on image processing. On the other hand, the visual clues or targets in the environment have different shapes and colors to indicate which task is available. Such targets are provided by a set of landmarks that change their color according to their availability. In particular, we can manipulate the delays to show a new available task in these landmarks. Each robot makes decisions about which type of target to search based on its experiences. Robots can double-check when they identify unclear images, which are also included in the image database. The proposed strategy for search and approach surpassed the hardware limitations allowing robot navigation with little visual information. A small improvement in the foraging mechanism allowed robots to achieve faster adaptations.
机译:搜索是满足任何觅食任务的关键活动之一。使用机器人时,大多数搜索策略都依赖于图像处理,这是最耗时的过程之一。在这项工作中,白鲨狩猎行为启发了一支觅食机器人团队的拟议战略,以搜索和接近物体。基于当前的感知,机器人可以通过在其传感器之间切换来加速觅食过程来接近其目标,即通过根据图像处理的较少。另一方面,环境中的视觉线索或目标具有不同的形状和颜色,以指示哪些任务可用。这些目标由一组地标提供,该地标根据其可用性而改变颜色。特别是,我们可以操纵延迟在这些地标中显示新的可用任务。每个机器人都会根据其经验做出关于搜索哪种类型的目标。机器人可以在识别图像数据库中的图像识别不清楚时仔细检查。拟议的搜索和方法策略超越了硬件限制,允许具有很少的视觉信息的机器人导航。觅食机构的少量改善允许机器人实现更快的适应。

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