发表机构
Carnegie Mellon University（卡内基梅隆大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
MOSAIC-SV提出一种基于规格先验的实时自适应动力学辨识与控制系统，无需专门试验即可在控制步中更新模型，仿真和实船试验表明其显著提升航行性能与预测精度。
AI 中文摘要
水生机器人平台基于模型的控制依赖于水动力模型，而该模型的辨识成本高昂，且仅适用于其测量时所对应的船体、载荷和条件。在此，我们提出MOSAIC-SV，一种可部署的实时自适应动力学辨识与控制系统，该系统从规格说明书工程先验出发辨识出足以支持控制的动力学模型，无需专门的辨识试验，并在闭环任务的每个控制步中重新估计该模型，同时控制器基于该模型进行规划。一个物理上可接受的无迹卡尔曼滤波器在闭环任务的每个控制步中重新估计水动力、扰动和执行器参数；而一个依赖于指令的考虑投影法会扣留当前指令无法在执行器效能与外部力之间归因的修正；一个模型预测路径积分控制器则基于当前估计进行规划。在CyberShip II仿真平台上，MOSAIC-SV在静态失配和瞬态变化下恢复了校准模型的航行性能，并且当其惯性或阻尼先验误差达一个数量级时，其航行时间仍保持在未缩放先验自身航行时间的20%以内。在Blue Robotics BlueBoat（一艘双推进器双体船）的实船试验中，MOSAIC-SV的航行速度至少快25%，且对其自身运动的预测误差至少比冻结工程先验低56%，包括在存在未建模载荷的情况下。相同的MOSAIC-SV系统概念也已成功部署在一艘6.3吨的双舷外机单体船上。
英文摘要
Model-based control of an aquatic robotic platform depends on a hydrodynamic model that is costly to identify and specific to the hull, payload, and conditions it was measured in. Here, we present MOSAIC-SV, a deployable real-time adaptive dynamics identification and control system that identifies a control-sufficient dynamics model from a spec-sheet engineering prior, without dedicated identification trials, and re-estimates it at every control step of a closed-loop mission while the controller plans on it. A physically admissible unscented Kalman filter re-estimates hydrodynamic, disturbance, and actuator parameters at every control step of the closed-loop mission; while a command-dependent consider projection withholds corrections the current command cannot attribute between actuator effectiveness and external force; and a model predictive path integral controller plans on the current estimate. In simulation on a CyberShip II plant, MOSAIC-SV recovers the transit performance of the calibrated model under static mismatch and transient changes, and stays within 20% of its own transit time at the unscaled prior when its inertia or damping prior is wrong by an order of magnitude. In on-water field trials on the Blue Robotics BlueBoat, a twin-thruster catamaran, MOSAIC-SV transits at least 25% faster and predicts its own motion with at least 56% less error than its frozen engineering prior, including under an unmodeled payload. The same MOSAIC-SV system concept was also feasibly deployed on a 6.3-tonne dual outboard monohull.
