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Mobile Robot''s Map Reconstruction Based on DSmT and Fast-Hough Self-Localization

机译:基于DSmT和快速自主定位的移动机器人地图重构。

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This paper presents a new tool based on DSmT (Dezert-Smarandache Theory) and fast-Hough self-localization which is applied to autonomous mobile robot''s map reconstruction. Uncertainty from sonar information is fused and managed in rebuilding grid map effectively with DSmT, since fast-Hough self-localization from laser information overcomes some shortcomings of classical Hough transformation including high amount of computation and low precision of localization. When a virtual mobile robot evolves in the virtual environment with different outline features, the result can adequately testify that the new tool owns better performance to rebuild map. In general, this research provides an approach for studying autonomous navigation of mobile robot or unmanned land vehicle (ULV) in unknown environment, also provides a human-computer interactive interface to manage and manipulate the robot remotely.
机译:本文提出了一种基于DSmT(Dezert-Smarandache理论)和快速霍夫自定位的新工具,该工具可用于自主移动机器人的地图重构。由于利用激光信息进行的快速霍夫自定位技术克服了传统霍夫变换的一些缺点,包括计算量大和定位精度低,因此,利用DSmT有效地重建声纳信息中的不确定性,并通过DSmT对其进行有效地管理。当虚拟移动机器人在具有不同轮廓特征的虚拟环境中发展时,结果可以充分证明新工具具有更好的重建地图性能。总的来说,这项研究提供了一种在未知环境中研究移动机器人或无人陆地车辆(ULV)的自主导航的方法,还提供了人机交互界面来远程管理和操纵机器人。

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