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Research on UAV path planning obstacle avoidance algorithm based on improved artificial potential field method

Qi BinKai, Mingqiu Li, Yang Yang, Xiyang Wang

2021Journal of Physics Conference Series23 citationsDOIOpen Access PDF

Abstract

Abstract In this paper, we study the path planning obstacle avoidance problem of UAV based on improved artificial potential field method (APF). By introducing dynamic adjustment coefficients, the gravitational force and repulsive force functions in the traditional APF are improved to make the obstacle avoidance safety factor higher and the final path smoother; for the target unreachability problem, a new attractive potential field is built in the gravitational force function to balance the changes of the traditional attractive force and repulsive force; a longitudinal random factor is used to solve the problem of getting into local minima. Through simulation comparison with other methods, this method can solve the path planning obstacle avoidance problem of UAV more efficiently.

Topics & Concepts

Obstacle avoidanceMaxima and minimaMotion planningObstaclePotential fieldPath (computing)Force field (fiction)Gravitational fieldComputer scienceField (mathematics)Collision avoidanceFunction (biology)Control theory (sociology)Mathematical optimizationAlgorithmArtificial intelligenceMathematicsPhysicsRobotMobile robotClassical mechanicsCollisionControl (management)LawEvolutionary biologyGeophysicsPure mathematicsMathematical analysisBiologyPolitical scienceComputer securityProgramming languageRobotic Path Planning AlgorithmsAutonomous Vehicle Technology and SafetyAutomated Road and Building Extraction