Kelasidi Eleni, Moe Signe, Pettersen Kristin Y, Kohl Anna M, Liljebäck Pål, Gravdahl Jan Tommy
Department of Engineering Cybernetics, Centre for Autonomous Marine Operations and Systems, Norwegian University of Science and Technology, Trondheim, Norway.
Department of Seafood Technology, SINTEF Ocean, Trondheim, Norway.
Front Robot AI. 2019 Jul 23;6:57. doi: 10.3389/frobt.2019.00057. eCollection 2019.
The use of unmanned underwater vehicles is steadily increasing for a variety of applications such as mapping, monitoring, inspection and intervention within several research fields and industries, e.g., oceanography, marine biology, military, and oil and gas. Particularly interesting types of unmanned underwater vehicles are bio-inspired robots such as underwater snake robots (USRs). Due to their flexible and slender body, these versatile robots are highly maneuverable and have better access capabilities than more conventional remotely operated vehicles (ROVs). Moreover, the long and slender body allows for energy-efficient transit over long distances similar to torpedo-shaped autonomous underwater vehicles (AUVs). In addition, USRs are capable of performing light intervention tasks, thereby providing intervention capabilities which exceed those of AUVs and inspection class ROVs. USRs may also propel themselves using energy-efficient motion patterns inspired by their biological counterparts. They can thereby increase the propulsion efficiency during transit and maneuvering, which is among the great challenges for autonomous underwater vehicles. In this paper, a control system for path following, and algorithms for obstacle detection and avoidance, are presented for a USR with thrusters attached at the tail module. The position of the obstacles is detected using a single camera in the head module of the USR and a developed computer vision algorithm. For the proposed control concept the robot joints are used for directional control while the thrusters are used for forward propulsion. The USR circumvents obstacles by following a circular path around them before converging back to the main straight line path when this is safe. Experimental results that validate the proposed methods are also presented.
无人水下航行器在多个研究领域和行业（如海洋学、海洋生物学、军事以及石油和天然气领域）的测绘、监测、检查和干预等各种应用中使用量正在稳步增加。特别有趣的无人水下航行器类型是受生物启发的机器人，比如水下蛇形机器人（USR）。由于其灵活且细长的身体，这些多功能机器人具有高度的机动性，并且比传统的遥控水下航行器（ROV）具有更好的进入能力。此外，细长的身体使得它们能够像鱼雷形状的自主水下航行器（AUV）一样，以节能的方式进行长距离航行。另外，水下蛇形机器人能够执行轻度干预任务，从而提供超过自主水下航行器和检查级遥控水下航行器的干预能力。水下蛇形机器人还可以利用受其生物同类启发的节能运动模式来推进自身。这样它们在航行和机动过程中可以提高推进效率，而这是自主水下航行器面临的重大挑战之一。本文针对一个在尾部模块安装了推进器的水下蛇形机器人，提出了一种路径跟踪控制系统以及障碍物检测和避障算法。利用水下蛇形机器人头部模块中的单个摄像头和一种开发的计算机视觉算法来检测障碍物的位置。对于所提出的控制概念，机器人关节用于方向控制，而推进器用于向前推进。水下蛇形机器人在障碍物周围绕圆形路径行驶以避开它们，当安全时再汇聚回到主直线路径。还给出了验证所提方法的实验结果。
