Intelligent Coordinated Motion Control of Underwater Robotic Vehicles with Manipulator Workpackages (Collaborative Research)

我们的主要研究目标是研究和开发具有机械手工作包的水下机器人（URVs）的智能控制策略。机械臂是附着在飞行器主体上的机械臂，它的运动影响着飞行器的运动，飞行器的动力学也受到参数不确定性、载荷和环境变化以及非线性行为的影响。有必要开发一种智能控制系统，为机器人运动和水下水流引起的机器人运动误差提供自动补偿。利用车辆的刻意运动对车辆和机械臂进行协调控制；这样的运动将有助于任务的执行，并将车辆的自由度增加到机械手工作包的自由度；对参数不确定性和环境变化的学习和适应能力；以及整个无人潜航器控制系统中高、低层子系统之间控制知识传递的紧密耦合。研究：扩展了水下机器人行走器和机械臂的理论建模，包括连杆与行走器主体的动态交互、运动冗余、系统与环境的接触稳定性以及无夹具操作；利用模糊聚类技术和在线强化学习技术，开发了基于模糊神经网络（FNN）控制的智能控制策略的理论框架；并在夏威夷大学的水下机器人飞行器ODIN（全方位智能导航员）上进行了实验演示。＊＊＊

9701850 Lee Our primary research objective is to investigate and develop intelligent control strategies for underwater robotic vehicles (URVs) with manipulator workpackages. The motion of the manipulator, which is attached to the vehicle's main body, affects the motion of the vehicle, whose dynamics are also subject to parameter uncertainties, changes in payload and environment, and nonlinear behavior. It is necessary to develop an intelligent control system for such vehicles to provide: automatic compensation for the errors of the vehicle motion, due to manipulator motion and underwater currents. coordinated control of both vehicle and manipulator using deliberate vehicle motion; such motion will help task performance and add the degrees of freedom of the vehicle to those of the manipulator workpackage; learning and adaptation capabilities to parameter uncertainties and changes in the environment; and close coupling of control knowledge transfer between the high-level and low-level subsystems of the overall URV control system. The study: extends a theoretical modeling of the underwater robotic vehicle and manipulator, including dynamic interaction between links and vehicle main body, kinematic redundancy, contact stability of the system in contact with the environment, and fixtureless manipulation; develops a theoretical framework for intelligent control strategies based on fuzzy neural network (FNN) control using fuzzy clustering techniques and on-line reinforcement learning technique; and includes experimental demonstration of the proposed approach on the University of Hawaii's underwater robotic vehicle, ODIN (Omni-Directional Intelligent Navigator). ***