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首页> 外文会议>Electrical and Electronics Engineering, 2009. ELECO 2009 >A new approach to improve the success ratio and localization duration of a particle filter based localization for mobile robots
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A new approach to improve the success ratio and localization duration of a particle filter based localization for mobile robots

机译：一种提高基于粒子滤波的移动机器人定位成功率和定位持续时间的新方法

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摘要

In real world applications, it is important that mobile robots know their location to achieve goals correctly. The localization of the robot is difficult by using raw sensor data because of the noisy measurements from these sensors. To overcome this difficulty probabilistic localization algorithm approaches can be used. The Particle filter is one of the Bayesian-based methods. In this study, two new features incorporated into the particle filter approach. These features are: decreasing the size of sample space using compass data and a new sensor model. The proposed approach is applied in the localization problem of a mobile robot. Performance of the proposed algorithm is compared with the performance of traditional particle filter approach by changing several parameters of the system. These analyses emphasized that the proposed approach improved the localization performance of the system. The results are promising for the future studies on this subject.
机译：在实际应用中，重要的是，移动机器人知道其位置才能正确实现目标。由于这些传感器的噪声测量结果，使用原始传感器数据很难对机器人进行定位。为了克服这个困难，可以使用概率定位算法方法。粒子过滤器是基于贝叶斯方法的一种。在这项研究中，两个新功能已合并到粒子过滤器方法中。这些功能包括：使用指南针数据和新的传感器模型减小样本空间的大小。所提出的方法被应用于移动机器人的定位问题。通过更改系统的几个参数，将所提算法的性能与传统粒子滤波方法的性能进行了比较。这些分析强调，所提出的方法改善了系统的本地化性能。该结果对于该主题的未来研究是有希望的。

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