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Path planning of mobile robot based on multi-sensor information fusion

机译:基于多传感器信息融合的移动机器人路径规划

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摘要

Mobile robot is a very important branch of robotics. In practice, the performance of mobile robot is required to be higher and higher. It is required that mobile robot can adapt to different complex environments through its own intelligent system to achieve the established functional goals. Compared with traditional path planning with single sensor information, Kalman filter is used to fuse multi-sensor information, and path planning method based on improved dynamic artificial potential field method is studied. Using the improved dynamic artificial potential field method, the robot can also achieve optimal path planning and obstacle avoidance in complex dynamic environment. The simulation results show that the proposed algorithm is feasible.
机译:移动机器人是机器人学的一个非常重要的分支。 在实践中,需要移动机器人的性能更高更高。 需要移动机器人通过自己的智能系统可以适应不同的复杂环境,以实现既定的功能目标。 与单个传感器信息的传统路径规划相比,卡尔曼滤波器用于熔断多传感器信息,研究了基于改进的动态人工潜在场方法的路径规划方法。 利用改进的动态人工潜在场方法,机器人还可以在复杂的动态环境中实现最佳路径规划和避免避免。 仿真结果表明,所提出的算法是可行的。

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