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A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments

机译:未知环境下自主水下航行器的实时反应避障算法

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摘要

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal.
机译:提出了一种新颖的实时反应避障算法(RRA),该算法基于前视声纳(FLS),用于必须适应未知复杂地形的自动水下航行器(AUV)。为了实现该算法,计划了避障规则,并将RRA过程分为五个步骤。简介仅列出了4个,因此AUV可以快速响应各种环境障碍。最大极角算法(LPAA)旨在将检测到的障碍物的不规则轮廓更改为凸多边形,从而简化了避障过程。设计了一种解决方案,通过轮廓记忆算法解决了U形避障中存在的陷阱问题。最后,在三个未知的障碍物场景上进行了仿真,以证明该算法的性能,所获得的避障轨迹是安全,平滑且接近最佳的。

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