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Path planning with fractional potential fields for autonomous vehicles

机译:路径规划与自动车辆的分数潜在领域

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Path planning is an essential stage for mobile robot control. It is more newsworthy than ever in the automotive context and especially for autonomous vehicle. Also, path planning methods need to be adaptive regarding life situations, traffic and obstacle crossing. In this paper, potential field methods are proposed to cope with these constraints and autonomous vehicles are considered equipped with all necessary sensors for obstacle detection. In this way, Ge&Cui's attractive potential field and fractional attractive potential field have been adapted to the context of autonomous vehicles. In this way, this latter method ensures better stability degree robustness with controlled vehicle acceleration.
机译:路径规划是移动机器人控制的重要阶段。它比以往任何时候都在汽车上下文中更为新闻价值,特别是对于自治车辆。此外,路径规划方法需要在生命情况,交通和障碍交叉方面是自适应的。在本文中,提出了应对这些限制的潜在场方法,并且认为自动车辆被认为是用于障碍物检测的所有必要传感器。通过这种方式,Ge&Cui的有吸引力的潜在场和分数有吸引力的潜在场已经适应自动车辆的背景。以这种方式,后一种方法确保了对受控车辆加速度的更好的稳定性鲁棒性。

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