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首页> 外文会议>Unmanned Systems Technology VIII pt.2 >An Adaptive Localization System for Outdoor/Indoor Navigation for Autonomous Robots
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An Adaptive Localization System for Outdoor/Indoor Navigation for Autonomous Robots

机译：自主机器人室外/室内导航的自适应定位系统

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摘要

Many envisioned applications of mobile robotic systems require the robot to navigate in complex urban environments. This need is particularly critical if the robot is to perform as part of a synergistic team with human forces in military operations. Historically, the development of autonomous navigation for mobile robots has targeted either outdoor or indoor scenarios, but not both, which is not how humans operate. This paper describes efforts to fuse component technologies into a complete navigation system, allowing a robot to seamlessly transition between outdoor and indoor environments. Under the Joint Robotics Program's Technology Transfer project, empirical evaluations of various localization approaches were conducted to assess their maturity levels and performance metrics in different exterior/interior settings. The methodologies compared include Markov localization, global positioning system, Kalman filtering, and fuzzy-logic. Characterization of these technologies highlighted their best features, which were then fused into an adaptive solution. A description of the final integrated system is discussed, including a presentation of the design, experimental results, and a formal demonstration to attendees of the Unmanned Systems Capabilities Conference n in San Diego in December 2005.
机译：移动机器人系统的许多预期应用要求机器人在复杂的城市环境中导航。如果机器人要在军事行动中与人类协同行动，则这一需求尤为重要。从历史上看，针对移动机器人的自主导航的开发既针对室外场景也针对室内场景，但并非同时针对这两种场景，这不是人类的操作方式。本文介绍了将组件技术融合到完整导航系统中的工作，使机器人可以在室外和室内环境之间无缝切换。在“联合机器人计划”的“技术转让”项目下，对各种本地化方法进行了经验评估，以评估其在不同外部/内部环境中的成熟度和性能指标。比较的方法包括马尔可夫定位，全球定位系统，卡尔曼滤波和模糊逻辑。这些技术的特性突出了它们的最佳功能，然后将其融合为自适应解决方案。讨论了最终集成系统的描述，包括设计演示，实验结果以及向2005年12月在圣地亚哥举行的无人系统能力会议n的参与者进行的正式演示。

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