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Multi-Ray Modeling of Ultrasonic Sensors and Application for Micro-UAV Localization in Indoor Environments

机译:超声传感器的多射线建模及其在室内微无人机定位中的应用

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摘要

Due to its payload, size and computational limits, localizing a micro air vehicle (MAV) using only its onboard sensors in an indoor environment is a challenging problem in practice. This paper introduces an indoor localization approach that relies on only the inertial measurement unit (IMU) and four ultrasonic sensors. Specifically, a novel multi-ray ultrasonic sensor model is proposed to provide a rapid and accurate approximation of the complex beam pattern of the ultrasonic sensors. A fast algorithm for calculating the Jacobian matrix of the measurement function is presented, and then an extended Kalman filter (EKF) is used to fuse the information from the ultrasonic sensors and the IMU. A test based on a MaxSonar MB1222 sensor demonstrates the accuracy of the model, and a simulation and experiment based on the ThalesII MAV platform are conducted. The results indicate good localization performance and robustness against measurement noises.
机译:由于其有效载荷,大小和计算限制,在室内环境中仅使用其机载传感器对微型飞行器(MAV)进行定位是一个具有挑战性的问题。本文介绍了一种室内定位方法,该方法仅依赖于惯性测量单元(IMU)和四个超声传感器。具体地,提出了新颖的多射线超声传感器模型以提供超声传感器的复杂波束图案的快速且准确的近似。提出了一种用于计算测量函数的雅可比矩阵的快速算法,然后使用扩展的卡尔曼滤波器(EKF)融合来自超声传感器和IMU的信息。基于MaxSonar MB1222传感器的测试证明了模型的准确性,并基于 T h a l e < / mi> s I I 开展MAV平台。结果表明良好的定位性能和对测量噪声的鲁棒性。

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