仿海龟机器人实现复杂海域自主追踪,可安全避障并监控活体海洋生物。
Autonomous Sea Turtle Robot for Marine Fieldwork
- 基于视觉的闭环控制,融合避障与目标跟踪
- 水族馆实验中障碍物避让成功率91%,能稳定追踪快速移动目标
- 首个在自然环境部署的仿生机器人,适合生态监测与海洋研究
自主机器人可变革海洋生态系统观测方式,但珊瑚礁等复杂环境中的近距离操作仍具挑战。车辆需在洋流、光照变化和感知受限条件下,安全靠近动物与脆弱结构。以往方法依赖柔性材料与仿生游动设计,但自主能力有限。本文提出一种仿海龟的自主水下机器人,通过紧密集成的视觉驱动控制栈,弥合了仿生运动与实地可用自主性之间的差距。该机器人具备稳定的深度-航向控制、障碍物规避与目标中心控制能力,可在复杂地形中追踪移动物体。我们在受控泳池与新英格兰水族馆的活珊瑚礁展区验证了其性能,展示了对快速移动海洋动物及人类潜水员的稳定追踪。据我们所知,这是首个集新颖硬件、控制算法与实地实验于一体的仿生机器人系统,成功在自然环境中追踪并监测真实海洋生物。在无缆实验中,机器人实现91%的障碍物避让成功率,并引入低算力机载追踪模式。这些成果为软硬混合、仿生水下机器人实现最小干扰探索与近距离监测提供了可行路径。
原文摘要 · Abstract (English)
Autonomous robots can transform how we observe marine ecosystems, but close-range operation in reefs and other cluttered habitats remains difficult. Vehicles must maneuver safely near animals and fragile structures while coping with currents, variable illumination and limited sensing. Previous approaches simplify these problems by leveraging soft materials and bioinspired swimming designs, but such platforms remain limited in terms of deployable autonomy. Here we present a sea turtle-inspired autonomous underwater robot that closed the gap between bioinspired locomotion and field-ready autonomy through a tightly integrated, vision-driven control stack. The robot combines robust depth-heading stabilization with obstacle avoidance and target-centric control, enabling it to track and interact with moving objects in complex terrain. We validate the robot in controlled pool experiments and in a live coral reef exhibit at the New England Aquarium, demonstrating stable operation and reliable tracking of fast-moving marine animals and human divers. To the best of our knowledge, this is the first integrated biomimetic robotic system, combining novel hardware, control, and field experiments, deployed to track and monitor real marine animals in their natural environment. During off-tether experiments, we demonstrate safe navigation around obstacles (91\% success rate in the aquarium exhibit) and introduce a low-compute onboard tracking mode. Together, these results establish a practical route toward soft-rigid hybrid, bioinspired underwater robots capable of minimally disruptive exploration and close-range monitoring in sensitive ecosystems.
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