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- W2765576410 abstract "本文通过采用激光测距仪获取周围环境的信息，运用迭代最近点(Iterative Closest Point, ICP)算法计算出位置，并通过对扩展卡尔曼滤波(Extended Kalman Filter, EKF)算法的改进，减少EKF算法的计算量，使旋翼飞行器能更加快速的实现对位置的估计。该算法通过在预测更新的过程中引进ICP算法计算的结果构建过程模型，并在测量更新过程中通过对环境中线段特征的提取，构建观测模型，结合飞控能够提供较为精确的角度信息的特点，简化观测模型的表达式，最终得到准确的位置信息。 In this paper, the environment information is captured and the position of rotorcraft is calculated by using laser scanner and using iterative closest point (ICP) algorithm. It could estimate the posi-tion more rapid and accurate by improving the extended Kalman filter (EKF) algorithm which re-duces the amount of computation. The trajectory model of rotorcraft will be constructed by com-bining and fusing the ICP and improved EKF algorithms to update the prediction. In the process of updating, the observed environment model will be sketched through extracting line features for surrounding of the rotorcraft. Then the model expression is simplified according to the accurate attitude angles of rotorcraft which come from Inertial Measurement Unit (IMU) sensor. Finally, location information is estimated accurately for the rotorcraft via simulation and experiment." @default.
- W2765576410 created "2017-11-10" @default.
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- W2765576410 date "2017-01-01" @default.
- W2765576410 modified "2023-09-24" @default.
- W2765576410 title "Position Estimation Algorithm for Rotorcraft Based on Laser Range Finder" @default.
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- W2765576410 doi "https://doi.org/10.12677/dsc.2017.64024" @default.
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