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A novel approach in Optimal trajectory identification for Autonomous driving in racetrack

机译:一种新的赛道自主驾驶最佳轨迹识别的新方法

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The autonomous vehicle is one of the greatest challenges in modern vehicle design. This paper proposes a new technique to define the optimal trajectory in a feedback form for an autonomous car, moving on a track. The algorithm defines the trajectory taking into the account the vehicle dynamic instead of kinematic constraints, leading to a more robust path. The technique is also used to control the vehicle in feedback, providing the optimal maneuvers to track the defined path. The method is based on the control law named FLOP, Feedback Local Optimality Principle, recently developed by the authors. The technique, starting from the Pontryagin's theory, introduces a new optimality principle that minimizes a sequence of individual functionals with the chance of a direct feedback control. The control acts on the steering and torques of a two-wheeled vehicle.
机译:自主车辆是现代车辆设计中最大的挑战之一。本文提出了一种新的技术,可以在自动驾驶的反馈形式中定义最佳轨迹,在轨道上移动。该算法将轨迹定义为账户中的轨迹动态而不是运动约束,导致更强大的路径。该技术还用于控制反馈中的车辆,提供最佳的动作以跟踪限定的路径。该方法基于名为FLOP的控制法,反馈本地最优原理,最近由作者开发。从Pontryagin的理论开始,该技术介绍了一种新的最优原理,可最大限度地减少一系列个别功能,具有直接反馈控制的可能性。控制作用于两轮车辆的转向和扭矩。

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