Abstract
We describe an integrated local path planning method whereby a particle filter is used for computation of the steering direction based on the Vector Field Histogram. In the original VFH, a typical polar histogram contains peaks (i.e., sectors) with a high polar obstacle density (POD) and valleys (i.e., sectors) that contain low polar obstacle density. In order to determine a desired path allowable for the width of the vehicle, the valley below some threshold is selected for the traversable local path. In the proposed approach, the particle filter is used to select the widest valley without the predefined threshold over the polar histogram and the measurement model of the particle filter is used for the uncertainty of each cell in the VFH as well. Experimental results from a mobile robot traversing the obstacle courses demonstrate the proposed approach successfully selecting and driving the most traversable path.
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