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

机译:动态规划的海上自主水面舰艇运动计划避撞和速度优化

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摘要

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:近年来,具有先进制导,导航和控制功能的海上自主水面舰艇(MASS)引起了极大的关注。安全有效地航行是MASS自主控​​制的关键要求。 MASS利用它所配备的雷达,摄像机和自主识别系统(AIS)收集的信息。本文研究了MASS的最佳运动计划问题,以便与其他常规船舶一起航行时,它可以尽早安全地完成航行任务。我们针对动态和静态障碍物开发了速度障碍物模型,以表示与其他对象的潜在无冲突区域。提出了一种基于速度障碍模型的基于贪婪区间的运动计划算法,该算法表明贪婪方法可能无法避免连续区间的冲突。提出了一种路障度量方法来评估碰撞风险,以改进贪婪算法。然后,通过假设周围船舶的速度恒定,提出了一种新颖的动态规划(DP)方法来为MASS生成最优的多间隔运动计划。通过广泛的仿真验证了这些提出的算法,表明与贪婪方法相比,DP算法提供了最低的总体碰撞率和更好的航行效率。

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