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Contour reconstruction using recursive smoothing splines - Algorithms and experimental validation

机译:使用递归平滑样条线进行轮廓重建-算法和实验验证

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摘要

In this paper, a recursive smoothing spline approach for contour reconstruction is studied and evaluated. Periodic smoothing splines are used by a robot to approximate the contour of encountered obstacles in the environment. The splines are generated through minimizing a cost function subject to constraints imposed by a linear control system and accuracy is improved iteratively using a recursive spline algorithm. The filtering effect of the smoothing splines allows for usage of noisy sensor data and the method is robust to odometry drift. The algorithm is extensively evaluated in simulations for various contours and in experiments using a SICK laser scanner mounted on a PowerBot from ActivMedia Robotics.
机译:本文研究了一种用于轮廓重建的递归平滑样条方法。机器人使用定期的平滑样条曲线来逼近环境中遇到的障碍物的轮廓。通过最小化受线性控制系统施加的约束的成本函数来生成样条,并使用递归样条算法迭代地提高精度。平滑样条的滤波效果允许使用噪声传感器数据,并且该方法对于里程表漂移具有鲁棒性。使用安装在ActivMedia Robotics的PowerBot上的SICK激光扫描仪,在各种轮廓的仿真和实验中对该算法进行了广泛的评估。

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