Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio telemetry equipment to locate low-power radio transmitters attached to wildlife from the ground. Although aerial robots can transform labor-intensive conservation tasks, the realization of autonomous systems for tackling task complexities under real-world conditions remains a challenge. We developed ConservationBots-small aerial robots for tracking multiple, dynamic, radio-tagged wildlife. The aerial robot achieves robust localization performance and fast task completion times -- significant for energy-limited aerial systems while avoiding close encounters with potential, counter-productive disturbances to wildlife. Our approach overcomes the technical and practical problems posed by combining a lightweight sensor with new concepts: i) planning to determine both trajectory and measurement actions guided by an information-theoretic objective, which allows the robot to strategically select near-instantaneous range-only measurements to achieve faster localization, and time-consuming sensor rotation actions to acquire bearing measurements and achieve robust tracking performance; ii) a bearing detector more robust to noise and iii) a tracking algorithm formulation robust to missed and false detections experienced in real-world conditions. We conducted extensive studies: simulations built upon complex signal propagation over high-resolution elevation data on diverse geographical terrains; field testing; studies with wombats (Lasiorhinus latifrons; nocturnal, vulnerable species dwelling in underground warrens) and tracking comparisons with a highly experienced biologist to validate the effectiveness of our aerial robot and demonstrate the significant advantages over the manual method.

翻译：如今，最广泛、最通用的数据采集技术仍依赖经验丰富的科学家手持无线电遥测设备，从地面定位附着在野生动物身上的低功率无线电发射器。尽管空中机器人能够变革劳动密集型的保护任务，但在现实条件下实现应对任务复杂性的自主系统仍是一项挑战。我们开发了ConservationBots——用于跟踪多个动态无线电标记野生动物的小型空中机器人。该空中机器人在实现鲁棒定位性能的同时，能快速完成任务——这对能量受限的空中系统至关重要，同时避免了与野生动物可能产生的反效干扰近距离接触。我们的方法克服了将轻量传感器与以下新概念结合所带来的技术及实际问题：i) 基于信息论目标进行规划，同时确定轨迹和测量动作，使机器人能够战略性选择近瞬时距离测量以实现快速定位，并选择耗时传感器旋转动作以获取方位测量值，实现鲁棒跟踪性能；ii) 对噪声更鲁棒的方位检测器；iii) 对现实条件下常见的漏检和虚警具有鲁棒性的跟踪算法。我们开展了广泛研究：基于复杂信号传播与多地形高分辨率高程数据的仿真实验、实地测试、针对袋熊（Lasiorhinus latifrons；夜行性、脆弱物种，栖息于地下洞穴）的研究，以及与经验丰富的生物学家的跟踪对比，验证了空中机器人的有效性，并展示了其相对于手动方法的显著优势。