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A geometric model for fusing IMU into monocular visual localization of 3-D mobile robots

机译:将IMU融合到3-D移动机器人的单眼视觉定位中的几何模型

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For the localization problem of mobile robots in 3D space, vision-based methods are being extensively investigated in recent years, due to the information richness provided by images. To improve the robustness and continuity, usually more sensors are introduced to assist visual localization in practices. In this paper, we propose a geometric model of fusing IMU data into the visual tracking process to estimate the robot trajectory in 3-D space. The model employs tracking of a certain number of feature points in the environment, and fuses them with sensor data from IMU to perform iterative adaptive estimation of both the robot trajectory and the positions of the selected feature points. The convergence and performance of the proposed method is validated in theoretical proof and simulation test.
机译:对于移动机器人在3D空间中的定位问题,由于图像提供的信息丰富,近年来基于视觉的方法已得到广泛研究。为了提高鲁棒性和连续性,通常会引入更多的传感器来辅助实践中的视觉定位。在本文中,我们提出了一种将IMU数据融合到视觉跟踪过程中的几何模型,以估计3-D空间中的机器人轨迹。该模型采用了对环境中一定数量特征点的跟踪,并将它们与来自IMU的传感器数据融合在一起,以对机器人轨迹和所选特征点的位置执行迭代自适应估计。理论证明和仿真测试均验证了该方法的收敛性和性能。

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