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The vector field histogram-fast obstacle avoidance for mobile robots

机译:移动机器人的矢量场直方图-快速避障

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摘要

A real-time obstacle avoidance method for mobile robots which has been developed and implemented is described. This method, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. The VFH method uses a two-dimensional Cartesian histogram grid as a world model. This world model is updated continuously with range data sampled by onboard range sensors. The VFH method subsequently uses a two-stage data-reduction process to compute the desired control commands for the vehicle. Experimental results from a mobile robot traversing densely cluttered obstacle courses in smooth and continuous motion and at an average speed of 0.6-0.7 m/s are shown. A comparison of the VFN method to earlier methods is given.
机译:描述了已开发并实现的用于移动机器人的实时避障方法。这种称为矢量场直方图(VFH)的方法可以检测未知的障碍并避免碰撞,同时将移动机器人转向目标。 VFH方法使用二维笛卡尔直方图网格作为世界模型。该世界模型不断更新,并通过车载范围传感器采样到范围数据。 VFH方法随后使用两阶段的数据缩减过程来计算车辆所需的控制命令。显示了移动机器人以平稳和连续运动,平均速度为0.6-0.7 m / s穿越密集杂乱的障碍物路线的实验结果。给出了VFN方法与早期方法的比较。

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