Distributed panoramic sensing in multiagent robotics

M. J. Barth, H. Ishiguro
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引用次数: 16

Abstract

In the field of multiagent robotics, much emphasis has been placed on explicit communication strategies between robots, and little on sensing. Sensing is often used on individual robots for avoiding obstacles, however the authors believe its use at a higher level can be advantageous for multiagent cooperation. The authors introduce a concept of cooperation by observation that features the use of panoramic vision sensing applied to multiagent robotics. Using panoramic vision techniques, a robot can view 360/spl deg/ around itself and also obtain coarse range information to objects in its environment. By also observing other robots in the robot society, localizing oneself within the group can be achieved. Thus each robot can observe its local area and create a local map. These distributed local maps centered around each robot can then be integrated into a larger global map based on the relative localization information between robots. Further, by sensing the positions of other robots and objects, a set of simple behaviors can be used to effectively explore the environment. Each robot calculates the range uncertainty to objects while viewing, and then moves to minimize that uncertainty. Multiagent exploration based on these behaviors has been shown to be effective through preliminary experimentation.<>
多智能体机器人中的分布式全景传感
在多智能体机器人领域中,很多重点放在机器人之间明确的通信策略上,而很少关注感知。传感通常用于单个机器人躲避障碍物,但作者认为,在更高层次上使用它可以有利于多智能体合作。作者介绍了一个观察合作的概念,该概念以全景视觉传感应用于多智能体机器人为特点。利用全景视觉技术,机器人可以观察自身360度/spl度/周围,并获得其环境中物体的粗略距离信息。通过观察机器人社会中的其他机器人,可以将自己定位在群体中。因此,每个机器人都可以观察其局部区域并创建局部地图。这些以每个机器人为中心的分布式局部地图,然后可以基于机器人之间的相对定位信息集成到更大的全球地图中。此外,通过感知其他机器人和物体的位置,一组简单的行为可以用来有效地探索环境。每个机器人在观察时计算物体距离的不确定性,然后移动以最小化不确定性。初步实验表明,基于这些行为的多智能体探索是有效的。
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