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A Real-Time Obstacle Avoidance Method for Autonomous Vehicles Using an Obstacle-Dependent Gaussian Potential Field

机译:基于障碍物的高斯势场的自动驾驶车辆实时避障方法

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A new obstacle avoidance method for autonomous vehicles called obstacle-dependent Gaussian potential field (ODG-PF) was designed and implemented. It detects obstacles and calculates the likelihood of collision with them. In this paper, we present a novel attractive field and repulsive field calculation method and direction decision approach. Simulations and the experiments were carried out and compared with other potential field-based obstacle avoidance methods. The results show that ODG-PF performed the best in most cases.
机译:设计并实现了一种新的自动驾驶汽车避障方法,称为依赖于障碍物的高斯势场(ODG-PF)。它检测障碍物并计算与它们碰撞的可能性。在本文中,我们提出了一种新颖的吸引力场和排斥场的计算方法和方向决策方法。进行了仿真和实验,并与其他潜在的基于场的避障方法进行了比较。结果表明,ODG-PF在大多数情况下表现最佳。

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