For the particle degeneracy problem of mobile robot simultaneous localization and mapping algorithm using Rao-Blackwellized particle filter (RBPF-SLAM), this paper proposed an improved sampling strategy.
针对采用Rao-Blackwellized粒子滤波器的移动机器人同步定位与地图构建算法（RBPF-SLAM）所面临的粒子退化问题，提出了一种改进的采样方法。
参考来源 - 基于固定滞后Gibbs采样粒子滤波的移动机器人SLAM—《计算机应用研究》—2008年第11期—龙源期刊网·2,447,543篇论文数据，部分数据来源于NoteExpress
Roboticists have developed tools to accomplish this task, known as simultaneous localization and mapping, or SLAM.
机器人研究专家已经开发出了一些来完成这项任务的工具，比如同步定位和勘测或者是SLAM。
Feature-based mobile robot simultaneous localization and mapping (SLAM) is an open problem in the field of robotics.
基于环境特征的移动机器人即时定位与地图创建是机器人领域的开放性课题。
Simultaneous localization and mapping (SLAM) is the key technique in autonomous navigation field and has become a hot issue for mobile robot.
同步定位与地图创建(SLAM)就是实现这一能力的关键技术，是机器人定位领域的热门研究课题之一。
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