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An Optimized Coverage Robot SLAM Algorithm Based on Improved Particle Filter for WSN Nodes

机译:基于改进粒子滤波器的WSN节点的优化覆盖机器人SLAM算法

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In order to realize the positioning and creation of the environment of mobile robots, this article proposes an optimized coverage robot SLAM algorithm based on an improved particle filter for WSN nodes. The algorithm overcomes the disadvantages of the standard particle filter SLAM algorithm in the simultaneous positioning of robot poses and creation of environmental maps. By constructing the sensor node to cover the high coverage of the SLAM positioning information node of the robot, the algorithm can search for the ideal result under the existing information, and the local optimization is performed to obtain the ideal result in another local state. Thus, the global accurate robot SLAM information is finally obtained. Simulation experiments show that the influence of the time delay parameter for simultaneous positioning of the robot SLAM is almost zero at different speeds, which shows the superior positioning stability of the new algorithm.
机译:为了实现移动机器人环境的定位和创造,本文提出了一种基于WSN节点的改进粒子滤波器的优化覆盖机器人SLAM算法。该算法克服了标准粒子滤波器SLAM算法在机器人姿势和创建环境贴图中的缺点。通过构造传感器节点以覆盖机器人的SLAM定位信息节点的高覆盖,可以在现有信息下搜索理想结果,并且执行局部优化以获得另一个本地状态的理想结果。因此,最终获得全局准确的机器人SLAM信息。仿真实验表明,在不同速度下,机器人LAM同时定位时延参数的影响几乎为零,这表示新算法的卓越定位稳定性。

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