Proposal of plug and play ego-motion estimator for mobile robot

Proposal of plug and play ego-motion estimator for mobile robot
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移动机器人即插即用自我运动估计器的提案

DOI:
10.1109/isccsp.2010.5463404
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发表时间:
2010
期刊:
2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP)
影响因子:
--
通讯作者:
T. Shimizu
T. Shimizu
中科院分区:
--
文献类型:
--
作者:
N. Suganuma;Y. Hayashi;T. Shimizu

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本文针对移动机器人的自运动估计问题,提出了一种即插即用的自运动估计器,用户可以自由选择传感器类型并灵活安装传感器。在该算法中,每个传感器都有一个传感器单元,每个传感器单元都有一些计算设备,每个传感器单元估计自我运动和传感器参数。此外,传感器单元通过网络连接,并相互交换每个单元的自运动估计。然后用协方差相交法对交换的信息进行融合,协方差相交法是一种分散估计方法。因此,该算法可以估计出不受传感器数量和传感器类型影响的自运动。此外,该算法在每个单元中估计传感器参数,并相互交换补偿信息,用户可以灵活地安装传感器。实验结果表明,该方法具有较高的灵活性,能较好地估计自运动。
In this paper, for an ego-motion estimating problem of mobile robot, we propose a plug and play ego-motion estimator that a user can freely select the sensor type and flexibly install the sensor. In this algorithm, each sensor is dealt with a sensor unit that has some computing equipment, and each sensor unit estimates the ego-motion and the sensor parameter. Moreover, the sensor units are connected via a network, and the ego-motion estimate of each unit are exchanged each other. Then the exchanged information is fused by Covariance Intersection method, which is one of a decentralized estimator. By this, this algorithm can estimate ego-motion not affected by number of sensors and sensor type. Furthermore, user can flexibly install the sensors by this algorithm because sensor parameters are estimated in each unit and compensated information are exchanged each other. In addition to this high flexibility, an experimental results denotes that our method estimate ego-motion with adequate accuracy.
基于去中心化数据关联的模块化车辆3D航位推算
DOI: --
发表时间: 2003
期刊: Transaction of the Japan Society of Mechanical Engineers 69-677 (Series C)
影响因子: --
作者:
Masafumi Hashimoto
通讯作者: Masafumi Hashimoto
DOI: 10.1109/robot.2003.1241884
发表时间: 2003-11
期刊: 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422)
影响因子: --
作者:
K. Ohno;T. Tsubouchi;Bunji Shigematsu;S. Maeyama;S. Yuta
通讯作者: K. Ohno;T. Tsubouchi;Bunji Shigematsu;S. Maeyama;S. Yuta