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Network-Centric Control for Multirobot Teams in Urban Search and Rescue

机译:以城市搜救和救援的多机罗多夫团队为中心控制

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Theories from Network-centric Warfare (NCW) distinguish between network-centric and platform--centric orientations to sensing and control. In platform-centric control the operator(s) access and focus on data through platforms they control, a robot's camera, for example. In network-centric control the operator(s) do not access data through platforms but instead through the network without regard to where information originated. The conventional human role in sophisticated information gathering systems is usually as both commander (of platforms) and perceiver. Human sensory and perceptual capabilities, however, far outstrip our abilities to process information frequently making our perceptual function more critical to the mission. The use of human operators as "perceptual sensors" is standard practice for both UAVs and ground robotics where humans are called upon to "process" camera video to find targets and assist in navigation. This paper traces the evolution of an experimental human-multirobot system for Urban Search and Rescue from a platform--centric implementation in which operators navigated robots while searching for victims in streaming video to a network--centric version in which they search recorded video asynchronously. We describe two lines of research leading to our current design. In the first we identify the navigation task as both more difficult and the limiting factor in extending control to larger robot teams. In the second we found a few strategically selected images viewed asynchronously roughly comparable in performance to continuously viewed streaming video.
机译:从网络为中心的战争(NCW)的理论区分以网络为中心和以平台为中心的方向来传感和控制。例如,在以平台为中心的控制操作员访问和专注于通过他们控制的平台,例如机器人的相机的数据。在以网络为中心的控制中,操作员不会通过平台访问数据,而是通过网络而不考虑到源自信息的位置。在复杂的信息收集系统中的传统人类角色通常是指挥官(平台)和感知者。然而,人类感官和感知能力远远超过我们的能力,以便经常使我们的感知函数对使命更为重要。人类运营商作为“感知传感器”是无人机和地面机器人的标准实践,其中人被要求“过程”相机视频以查找目标并协助导航。本文跟踪了城市搜索和救援的实验人类多利用系统的演变,从一个平台的实现,运营商正在进行机器人,同时在将视频中搜索流向网络的受害者,其中他们以异步搜索录制的视频。 。我们描述了两种研究领导我们目前的设计。首先,我们将导航任务确定为更困难和对更大的机器人团队扩展控制的限制因素。在第二个我们发现一些策略性选择的图像在性能中异步地大致相当地观看,以便连续观看的流式视频。

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