The traditional artificial potential field algorithm has the shortcomings of appearing trap area easily and shaking
in front of obstacles. This paper, studying traditional artificial potential field deeply, optimizes the sensor data with the
introduction of the BP network and the GA algorithm, unmanned vehicles achieving autonomous obstacle avoidance and
prognoses in advance when passing the path with obstacles, and effectively eliminating system instability caused by shock
and dead zone. Comparing with traditional artificial potential field algorithm, the improved algorithm makes a further improvement
in the respects of system stability and efficiency.
Keywords: BP network, GA algorithm, multi sensor, potential field method, unmanned vehicle.
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