Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning–based routing (autonomy module) and synthetic aperture radar–based very high frequency (VHF) signal–based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an “engineered whale”—a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists.

中文翻译：

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基于强化学习的框架，通过自主感应机器人进行鲸鱼会合


与抹香鲸会合进行生物观察因其长时间的潜水模式而变得具有挑战性。在这里，我们提出了一个算法框架，该框架共同开发基于多智能体强化学习的路由（自主模块）和基于合成孔径雷达的甚高频 （VHF） 信号方位估计（传感模块），以最大限度地提高自主机器人与抹香鲸的会合机会。传感模块与通常用于跟踪野生动物的低能耗 VHF 标签兼容。自主模块利用鲸鱼发声、VHF 标签和鲸鱼潜水行为的原位噪声方位测量，在模拟中实现机器人团队与多头鲸鱼的时间关键型会合。我们在抹香鲸的原生栖息地进行了海上实验，使用了“工程鲸鱼”——一艘配备了 VHF 发射标签的快艇，模拟了五种不同的鲸鱼轨迹，具有不同的鲸鱼运动。传感模块显示与标签的方位角中值误差为 10.55°。使用声学传感器和我们的传感模块对工程鲸鱼的方位测量，我们的自主模块在后处理中使用三个机器人，在 500 米的交会距离内提供 81.31% 的总交会成功率。第二类现场实验对三头未标记的抹香鲸使用纯声方位测量，结果显示，在后处理中使用两个机器人进行 1000 米交会距离的总交会成功率为 68.68%。我们使用海洋生物学家收集的抹香鲸视觉相遇数据集，通过几项消融研究进一步验证了这些算法。