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A novel fusion method for robot indoor environment mapping

机译:机器人室内环境测绘的融合方法

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In order to solve the stability of mapping of mobile robot, a fusion method based on Kalman Filter is proposed to reduce the accumulative errors during the mobile motion. This fusion method, which can fuse the sequential scan matching results and odometer measures, is suitable for raw points based scan matching method. In this paper, pose estimation results from raw points based scan matching method are viewed as the observation model, and odometer measures are viewed as the status model. Experimental results are shown to validate the effectiveness of the proposed approach.
机译:为了解决移动机器人映射的稳定性,提出了一种基于卡尔曼滤波的融合方法,以减少运动过程中的累积误差。这种融合方法可以融合顺序扫描匹配结果和里程表测量值,适用于基于原始点的扫描匹配方法。本文将基于原始点的扫描匹配方法的姿态估计结果视为观测模型,将里程表的测量结果视为状态模型。实验结果表明,验证了所提方法的有效性。

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