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Combining Complementary Motion Estimation Approaches to Increase Reliability in Urban Search ; Rescue Missions

机译:结合互补运动估计方法以提高城市搜索的可靠性救援任务

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Precise motion estimation is vital for any mobile robot to correctly control its actuators and thus to navigate through terrain. Bar sic approaches of motion estimation (e.g. wheel odometry) that can be considered reliable in laboratory conditions tend to fail in real-world search and rescue scenarios because of uneven and slippery surface the robot has to cross. In this article, we pick some of the current localization and motion estimation techniques and discuss their prerequisites in contrast with experience gathered during end-user evaluations and a real-world deployment of our robotic platform in a town struck by an earthquake (Mirandola, Italy). The robotic platform is equipped with a set of sensors allowing us to combine various approaches to robot localization and motion estimation in order to increase the redundancy in the system and thus the overall reliability. We present our approach to fuse selected sensor modalities that was developed with emphasis on possible sensor failures, which have been subsequently experimentally tested.
机译:精确的运动估计对于任何移动机器人正确地控制其执行器,从而在地形中导航至关重要。在实验室条件下被认为可靠的运动估计的基本方法(例如车轮里程计)在现实世界的搜索和救援场景中往往会失败,因为机器人必须穿越不平坦且光滑的表面。在本文中,我们选择了一些当前的本地化和运动估计技术,并与最终用户评估期间收集的经验以及在地震发生的城镇中对机器人平台的实际部署(意大利米兰多拉市)进行了对比,讨论了它们的先决条件。 )。机器人平台配备了一组传感器,使我们能够结合各种方法来进行机器人定位和运动估计,以增加系统的冗余度,从而提高整体可靠性。我们介绍了融合所选传感器形式的方法,该方法重点研究了可能出现的传感器故障,并随后进行了实验测试。

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