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Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization

机译:采用动态规划避雷和速度优化动态规划海上自主地面运动计划

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Maritime Autonomous Surface Ships (MASS) with advanced guidance, navigation, and control capabilities have attracted great attention in recent years. Sailing safely and efficiently are critical requirements for autonomous control of MASS. The MASS utilizes the information collected by the radar, camera, and Autonomous Identification System (AIS) with which it is equipped. This paper investigates the problem of optimal motion planning for MASS, so it can accomplish its sailing task early and safely when it sails together with other conventional ships. We develop velocity obstacle models for both dynamic and static obstacles to represent the potential conflict-free region with other objects. A greedy interval-based motion-planning algorithm is proposed based on the Velocity Obstacle (VO) model, and we show that the greedy approach may fail to avoid collisions in the successive intervals. A way-blocking metric is proposed to evaluate the risk of collision to improve the greedy algorithm. Then, by assuming constant velocities of the surrounding ships, a novel Dynamic Programming (DP) method is proposed to generate the optimal multiple interval motion plan for MASS. These proposed algorithms are verified by extensive simulations, which show that the DP algorithm provides the lowest collision rate overall and better sailing efficiency than the greedy approaches.
机译:海上自主地面船舶(质量)具有先进的指导,导航和控制能力近年来引起了极大的关注。安全有效地航行是对质量自主控制的关键要求。群众利用雷达,相机和自主识别系统(AIS)收集的信息。本文调查了质量最佳运动规划问题,因此当它与其他传统船只一起航行时,它可以提前和安全地完成其帆船任务。我们为动态和静态障碍开发速度障碍模型,以表示与其他物体的潜在不禁冲突区域。基于速度障碍(VO)模型提出了一种贪婪的间隔运动规划算法,我们表明贪婪的方法可能无法以连续的间隔避免碰撞。提出了一种阻塞度量来评估碰撞的风险,以提高贪婪算法。然后,通过假设周围船舶的恒定速度,提出了一种新的动态编程(DP)方法以产生质量的最佳多个间隔运动计划。这些所提出的算法通过广泛的模拟验证,这表明DP算法总体上的碰撞率最低,驾驶效率优于贪婪的方法。

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