An artificial-potential-field method for real-time UAV navigation in unknown environments

doi:10.7523/j.ucas.2020.0022

Abstract

Abstract: This paper proposes a local planning method for real-time obstacle avoidance in unknown environments. This method constructs a Dirichlet boundary value problem once the obstacle points are obtained from sensors. This problem is solved by FDM (finite difference method), and hence it generates a Laplacian potential field based on the local map. The potential field is replaced by a new one when the sensing data got updated. This construction can efficiently deal with complex environments, and there is no local minimum in the field. The reference velocities are generated by the directions of the negative gradient in the field, which are tracked by the PID controller, in order to achieve autonomous UAV (unmanned aerial vehicle)navigation. Finally, MATLAB experiments are taken under different scenes, and the result shows this method is valid for real-time obstacle avoidance in different unknown environments.

Key words: obstacle avoidance, autonomous navigation, Laplace’s equation, artificial potential field, Dirichlet problem, unmanned aerial vehicle (UAV)

CLC Number:

TP242

SONG Xiaocheng, LIU Xiaopei, LU Jie. An artificial-potential-field method for real-time UAV navigation in unknown environments[J]. Journal of University of Chinese Academy of Sciences, 2022, 39(3): 393-402.

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