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Online Robotic Exploration for Autonomous Underwater Vehicles in Unstructured Environments

机译:非结构化环境中自主水下车辆的在线机器人探索

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When it is not possible to use remotely operated vehicles (ROVs) or autonomous underwater vehicles (AUVs) with predefined missions to explore complex underwater structures, efficient and safe algorithms for autonomous online exploration are required. In this work we present a robotic exploration algorithm for AUVs which is able to autonomously explore 3D underwater structures. In our proposal, the explored structure must have vertical relief, and the exploration is performed in 2D at a user defined depth. No assumptions are made about the shape of the object, so this makes the algorithm particularly useful to explore unstructured environments. Our approach is able to plan the robot maneuvers to achieve full coverage of the scene with data from two sensors: a scanning profiling sonar, and a camera. The algorithm first incorporates the exteroceptive data from the profiler sonar into a labeled grid map. Then, different candidate viewpoints are generated and the best one is selected according to a metric that balances exploration and trajectory length. Once the best viewpoint has been selected, the robot navigates in the scene to achieve the selected viewpoint configuration. This procedure is repeated until the desired area has been fully explored. To validate our approach, we present simulated and real autonomous explorations of an underwater seamount.
机译:当不可能使用具有预定义的任务的远程操作的车辆(ROV)或自主水下车辆(AUV)以探索复杂的水下结构,需要有效和安全的在线勘探算法。在这项工作中,我们为AUV提供了一种机器人探索算法,其能够自主地探索3D水下结构。在我们的建议中,探索的结构必须具有垂直浮雕,并且在用户定义深度的2D中在2D中进行探索。没有对对象的形状进行假设,因此这使得算法特别有用探索非结构化环境。我们的方法能够规划机器人操作,以实现与来自两个传感器的数据完全覆盖场景:扫描分析声明和相机。该算法首先将来自Profiler Sonar的exteroplective数据包含在标记的网格图中。然后,生成不同的候选视点,并且根据余额勘探和轨迹长度的度量来选择最佳的候选视点。选择最佳视点后,机器人在场景中导航以实现所选视点配置。重复该过程,直到已完全探索所需的区域。为了验证我们的方法,我们提出了一个水下海山的模拟和真正的自主探索。

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