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Air-Ground Cooperative Environment Modeling with Bounded Elevation Map

机译:空域合作环境建模与有界高度地图

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UGVs' application are always restrained in complicated environment because of its limited perception ability. One of the solution is cooperation with UAV which has large perception scale. Thus, the fusion of the air-ground perceptive information is the key problem. Focused on this problem, the ESMF based 2.5D elevation modeling method is first proposed for its bound rather than probabilistic information is robust and reliable for path planning of UGVs. In the second, the fast fusion method between air and ground vehicles is designed, which achieve data fusion by updating the perception of UGV with UAV instead of intersecting the two observation sets. In the third the traversability is analyzed based on the elevation model described with bounded information, which shows the robust and reliable of the proposed method. In the last based on two typical limited perception ability: negative and ultrahigh obstacle an experiment is designed to verify the feasibility and validity of the propose method.
机译:无人地面车辆应用程序总是限制在复杂的环境中,因为其有限的感知能力。其中一个解决方案是用无人机具有较大规模的感知合作。因此,空气 - 地感知信息的融合是关键问题。专注于这个问题,基于ESMF 2.5D高程模型方法,首次提出了其必然,而不是概率信息是无人地面车辆的路径规划坚固可靠。在第二个,空中和地面车辆之间的快速融合方法被设计,其通过与的UAV代替交叉的两个观测集更新UGV的感知实现数据融合。在第三的通行性分析基于与有界信息,其示出了坚固和可靠的所提出的方法的描述的高程模型。在基于两种典型的有限的感知能力最后:负和超高障碍物的设计实验来验证提出方法的可行性和有效性。

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