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Fused quad audio/visual and tracking data collection to enhance mobile robot and operator performance analyses

机译:融合四路音频/视频和跟踪数据收集,以增强移动机器人和操作员的性能分析

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Collecting accurate, adequate ground truth and experimental data to support technology evaluations is critical in formulating exact and methodical analyses of the system's performance. Personnel at the National Institute of Standards and Technology (NIST), tasked with developing performance measures and standards for both Urban Search and Rescue (US&R) and bomb disposal robots, have been designing advanced ground truth data collection methods to support these efforts. These new techniques fuse multiple real-time streams of video and robot tracking data to facilitate more complete human robot interaction (HRI) analyses following a robot's experiences. As a robot maneuvers through a test method, video and audio streams are simultaneously collected and fed into a quad compressor providing real-time display. This fused quad audio/visual data provides a complete picture of what the operators and robots are doing throughout their evaluation to not only enhance HRI analyses, but also provide valuable data that can be used to aid operator training, encourage implementation improvements by highlighting successes and failures to the developers/vendors, and demonstrate capabilities to end-users and buyers. Quad data collection system deployments to support US&R test methods/scenarios at the 2007 Robot Response Evaluation in Disaster City, Texas will be highlighted.
机译:收集准确,充分的地面真相和实验数据以支持技术评估,对于制定对系统性能的精确而系统的分析至关重要。美国国家标准技术研究院(NIST)的工作人员,负责为城市搜索与救援(US&R)和炸弹处理机器人制定性能指标和标准,他们正在设计先进的地面真相数据收集方法来支持这些工作。这些新技术融合了视频和机器人跟踪数据的多个实时流,以促进根据机器人的体验进行更完整的人机交互(HRI)分析。当机器人通过测试方法进行操作时,视频和音频流将同时收集并馈入提供实时显示的四路压缩器中。这些融合的四路音频/视频数据可提供操作员和机器人在整个评估过程中所做工作的完整图片,不仅可以增强HRI分析,还可以提供有价值的数据,以帮助操作员培训,通过突出成功和改进来鼓励实施改进。开发人员/供应商的失败,并向最终用户和购买者展示能力。在2007年德克萨斯州灾难市机器人响应评估中,将重点介绍支持US&R测试方法/方案的四元数据收集系统部署。

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