A master-slave control system for a semi-autonomous underwater vehicle-manipulator system

Underwater vehicle-manipulator systems (UVMS) are expected to play an important role in ocean exploration. It is considered that UVMS will be operated by both automatic and manual control. We have proposed an automatic control method. In this article, we propose a master-slave system for a UVMS. The effectiveness of the proposed master-slave control system is demonstrated by using a floating underwater robot with a 2-link manipulator.     

Digital type disturbance compensation control of a floating underwater robot with 2 link manipulator

We have proposed continuous and discrete time resolved acceleration control methods for underwater vehicle-manipulator systems and the effectiveness of the control methods have been shown by experiments. In this paper, we propose a digital type disturbance compensation control method based on the RAC method considering singular configuration of manipulator. Experimental results show the effectiveness of the proposed method. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Trajectory Tracking Control of an Underactuated Underwater Vehicle Redundant Manipulator System

The purpose of this study is to control the position of an underactuated underwater vehicle manipulator system (U‐UVMS). It is possible to control the end‐effector using a regular 6‐DOF manipulator despite the undesired displacements of the underactuated vehicle within a certain range. However, in this study an 8‐DOF redundant manipulator is used in order to increase the positioning accuracy of the end‐effector. The redundancy is resolved according to the criterion of minimal vehicle and joint motions. The underactuated underwater vehicle redundant manipulator system is modeled including the hydrodynamic forces for the manipulator in addition to those for the autonomous underwater vehicle (AUV). The shadowing effects of the bodies on each other are also taken into account when computing the hydrodynamic forces. The Newton‐Euler formulation is used to derive the system equations of motion including the thruster dynamics. In order to establish the end‐effector trajectory tracking control of the system, an inverse dynamics control law is formulated. The effectiveness of the control law even in the presence of parameter uncertainties and disturbing ocean currents is illustrated by simulations.     

Neural networks to determine task oriented dexterity indices for an underwater vehicle-manipulator system

A method for the fast approximation of dexterity indices for given underwater vehicle-manipulator systems (UVMS) configurations is presented. Common underwater tasks are associated with two well-known dexterity indices and two types of neural networks are designed and trained to approximate each one of them. The method avoids the lengthy calculation of the Jacobian, its determinant and the computationally expensive procedure of singular value decomposition required to compute the dexterity indices. It provides directly and in a considerably reduced computational time the selected dexterity index value for the given configuration of the system. The full kinematic model of the UVMS is considered and the NN training dataset is formulated by the conventional calculation of the selected dexterity indices. A comparison between the computational cost of the analytical calculation of the indices and their approximation by the two NN is presented for the validation of the proposed approach. This paper contributes mainly on broadening the applications of NN to a problem of high complexity and of high importance for UVMS high performance intervention.     

Robust arm configuration of manipulator mounted on flexible base

In this paper, the robustness of a manipulator mounted on a flexible base with a task-space feedback control to a fixed desired point is considered. We define the robust arm configuration (RAC), which is a special configuration where the linearized system is positive real. Lyapunov indirect method and the passivity theory guarantee a local asymptotic stability of the original nonlinear system. A finite but high closed-loop gain can be applied in the neighborhood of the RAC without considering the base flexibility, i.e., an additional sensor or a solution of whole inverse dynamics is not necessary. Considering the positive semidefiniteness of the residue matrices, a measure is proposed that measures the distance from the RAC. This measure represents the controllability of the manipulator itself, and does not depend on the underlying control law. The validity of the proposed approach is confirmed by a numerical example and experiments.     

Adaptive nonsingular fast terminal sliding mode control for underwater manipulator robotics with asymmetric saturation actuators

In this paper, an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) is proposed for underwater manipulator robotics with asymmetric actuator saturations and unknown time-varying (TV) external disturbances. Firstly, the nonsingular fast terminal sliding mode (NFTSM) control scheme is conducted for the underwater manipulator robotics, which guarantees the boundedness of all the signals in the control system. Secondly, the adaptive method and the smooth hyperbolic tangent (tanh) function are introduced to address the unknown TV external disturbances and the input saturation errors. Thus the prior knowledge about the upper bounds of the system uncertainties is not needed in this paper. To deal with the nonlinear asymmetric input saturation issue, a Gaussian error function is employed in the asymmetric saturation module so that the discontinuous input signals can be transformed into smooth forms. Thirdly, the rigorous mathematical verification is conducted to demonstrate the stability and finite-time convergence of the closed-loop control system via the Lyapunov theory. Finally, numerical simulations are performed on a two-link underwater manipulator robotic system to illustrate the effectiveness of the proposed controller.     

基于RBF神经网络的作业型AUV自适应终端滑模控制方法及实验研究

研究了作业型AUV （自主水下机器人）的轨迹跟踪控制问题.实际作业中,水下机械手展开作业过程将引起AUV动力学性能变化,进而影响AUV轨迹跟踪控制;并且水流环境干扰亦将影响AUV轨迹跟踪控制.针对上述AUV轨迹跟踪控制问题,提出一种基于RBF （径向基函数）神经网络的AUV自适应终端滑模运动控制方法.该方法在李亚普诺夫稳定性理论框架下,采用RBF网络对机械手展开引起的AUV动力学性能变化和水流环境干扰进行在线逼近,并结合自适应终端滑模控制器对神经网络权值和AUV控制参数进行自适应在线调节.通过李亚普诺夫稳定性理论,证明AUV系统轨迹跟踪误差一致稳定有界.针对滑模控制项引起的控制量抖振问题,提出一种变滑模增益的饱和连续函数滑模抖振降低方法,以降低滑模控制量抖振.通过AUV实验样机的艏向和垂向的轨迹跟踪实验,验证了本文AUV系统控制方法和滑模降抖振方法的有效性.     

基于神经网络和模糊补偿的水下机械臂控制

针对水下机械臂动力学模型建模复杂且滑模控制的抖振问题,利用Lagrange法和Morison方程精准建立二连杆串联水下机械臂的动力学模型,对模型中参数的不确定项使用4个RBF神经网络分别进行逼近,并且对摩擦项使用模糊控制进行补偿的方法,精准迅速地实现了对水下机械臂控制系统跟踪控制。通过进行仿真分析,基于神经网络和模糊补偿控制的方法与滑模控制、整体RBF神经网络控制和分块RBF神经网络控制相比,控制系统的平均误差分别降低了85.5%、71.8%、93.1%。结果表明,此方法有效降低了控制系统的跟踪误差,并同时提高了稳态性和抗干扰性。     

A nonregressor nonlinear disturbance observer-based adaptive control scheme for an underwater manipulator

A new nonlinear disturbance observer-based tracking control scheme for an underwater manipulator is presented in this paper. This observer overcomes the disadvantages of existing disturbance observers, which are designed or analyzed by the linear system techniques. It can be applied in underwater manipulator systems for various purposes such as payload compensation, interaction effects compensation, underwater current or external disturbance compensation, and independent system control. The performance of the proposed tracking control scheme is demonstrated numerically by the payload compensation and interaction effects compensation for a two degrees of freedom vertical underwater manipulator.     

Experiments on a floating underwater robot with a two-link manipulator

This article concerns experiments with a free-floating underwater robot with a two-dimensional, horizontal planar, two-link manipulator. Some dynamic models of underwater manipulators have been proposed, but only a few experiments have been carried out. Here, we derive a dynamic model for a free-floating underwater robot with a two-link manipulator, including the hydrodynamic forces, and validate the effectiveness of the model by simulation and experiment. We also show an experimental result using a resolved acceleration control method. These experimental results show the effectiveness the model and the control method. This work was presented in part at the 5th International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

基于能耗优化的深海电动机械臂轨迹规划

由于深海电动机械臂动力学模型较为复杂,难以基于动力学模型构建精确的能耗优化目标函数,因此,本文提出一种利用径向基函数（RBF）神经网络构建机械臂功耗模型的方法．首先,利用机械臂水下运动实验数据集训练所构建的RBF神经网络．利用基于该神经网络的功耗模型,结合机械臂关节空间轨迹规划多项式,建立机械臂能耗目标函数．然后,采用自适应粒子群优化（PSO）算法求解最优轨迹参数．结果显示,RBF功耗网络均方根误差（RMSE）为20.89 W;经过优化的轨迹的能耗比实验轨迹的能耗均值降低410.8 J（18.3%）．实验结果表明基于自适应PSO算法的轨迹规划方法实现了能耗优化的目标．     

Kinematic Design and Analysis of a 7 Degree-of-Freedom Dual-Stage Inspection Manipulator for Dexterous Subsea Applications

This paper describes the design of a 7 degree-of-freedom (d.o.f) manipulator for underwater inspection applications. The functional requirements of an underwater manipulator for subsea inspection are discussed and the desired performance requirements identified. The inspection process of a weld joint using a manipulator is described and the desirable attributes of a 5 d.o.f manipulator for the inspection process established. A novel kinematic structure, for Underwater Robotic Vehicle (URV) operation, having a 2 d.o.f launching stages and a 5 d.o.f inspection stage is proposed for the manipulator. This configuration increases the dexterity, without compromising on the total reach of the manipulator. The kinematic structure of the 7 d.o.f, 2 stage, manipulator is presented. A hybrid power actuation is proposed for the manipulator to exploit the benefits of both hydraulic as well as electric actuators. Kinematic analysis of the manipulator is presented. The link dimensions of the inspection stage manipulator is done on the basis of kinematic performance indices of the manipulator. The novel kinematic structure and the hybrid power actuation strategy results in a power efficient, dexterous manipulator for underwater applications.     

Position/Force Control of an Underwater Mobile Manipulator

This paper proposes a new control method applied to an underwater vehicle equipped with a robot manipulator. This control method is based on force control to stabilize the platform when the manipulator works in free or constrained space. The torque produced by the arm on the platform is estimated with a force sensor installed between the base of the manipulator and the vehicle. This allows correcting the position errors of the platform using an external force control loop. This paper presents this control law and shows some simulation results. © 2003 Wiley Periodicals, Inc.     

基于深度强化学习与多参数域随机化的水下机械手自适应抓取研究

以水下机械手自主作业的应用需求为背景,针对水下机械手动力学参数时变、工作环境复杂、传感器限制、控制精度低等问题,基于强化学习与多参数域随机化理论提出一个具有通用性的水下机械手作业框架。首先,建立基本的机器人强化学习控制系统,然后采用多参数域随机化方法增强强化学习训练策略的稳定性与策略迁移效果,包括机械手动力学参数、水动力参数、状态空间与动作空间的噪声和延时等;最后,将训练的策略分别迁移到一个新的机器人仿真环境与一款真实的工作级水下机械手上进行实验。大量实验验证了本文所提方法的有效性,为未来真实海域自主作业奠定了基础。     

Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

The underwater swimming manipulator (USM) is a snake‐like, multi‐articulated, underwater robot that is equipped with thrusters. One of the main purposes of the USM is to act like an underwater floating base manipulator. As such, it is essential to achieve good station‐keeping and trajectory tracking performance for the USM by using the thrusters and by using the joints to attain the desired position and orientation of the head and tail of the USM. In this ‘paper, we propose a sliding mode control (SMC) law, specifically the super‐twisting algorithm with adaptive gains, for the trajectory tracking of the USM's centre of mass. A higher‐order sliding mode observer is proposed for state estimation. Furthermore, we show the ultimate boundedness of the tracking errors. We demonstrate the applicability of the proposed control law and show that it leads to better performance than a linear PD‐controller.     

Task space-based control of an underwater robotic system for position keeping in ocean currents

For an underwater vehicle-manipulator system, which consists of an underwater vehicle equipped with a manipulator, it is important to regulate the position of the manipulator’s end-effector with respect to a given target position in many interactive operations. This paper presents a task space-based approach for designing a controller that ensures that the end-effector of an underwater vehicle-manipulator system maintains its position in the presence of unknown ocean currents and uncertainties without the explicit use of a disturbance observer. A feedback linearizing control in task coordinates is used, and an extended Kalman filter (EKF) is employed as a state observer. The proposed approach can also be applied to dynamic positioning or controlled weathervaning of a surface ship whose motion is affected by environmental disturbances. To demonstrate the validity and effectiveness of the proposed approach, numerical simulations and experimental tests were carried out and their results are shown.     

Digital RAC for underwater vehicle-manipulator systems considering singular configuration

We have proposed continuous-time and discrete-time resolved acceleration control methods for underwater vehicle-manipulator systems and the effectiveness of the control methods has been shown by experiments. In this article, we propose a digital control method considering the singular configuration of manipulator. Experimental results show the effectiveness of the proposed method. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

水下焊接机器人变质心补偿控制

为了补偿由于3自由度直角坐标式机械臂移动引起的HITUWV水下焊接机器人质心变化,提出基于变质心模型的自适应滑模控制方法（CVM-ASMC）．首先建立机器人变质心模型,精确地描述水下焊接机器人的变质心特性．随后,设计基于变质心模型的自适应滑模控制器,实现高精度变质心补偿．实验结果表明,相较于传统PID（比例－积分－微分）控制器与基于模型的PID控制器,提出的CVM-ASMC具有更高的精确性、更好的稳定性以及更低的能耗．因此,CVM-ASMC可以满足水下作业稳定与高精度运动控制要求．     

基于人机交互的重载机械臂控制方法

针对目前重载机械臂控制系统存在的人机交互性不足问题及重载带来的刚柔耦合问题,设计了一种基于动力学模型的人机交互闭环力!/!位控制算法,并依据该算法设计了7自由度重载机械臂控制系统.首先分析了国内外重载机械臂的工作特点和存在的问题,提出基于力!/!视觉反馈的人机交互方式来增强系统的人机交互性;然后为抑制刚柔耦合带来的控制问题,建立了重载机械臂刚柔耦合动力学模型,提出基于人机交互的重载机械臂力!/!位闭环控制算法.最后搭建重载机械臂控制系统,搭建的控制系统包括人机交互子系统、环境感知子系统、驱动子系统、信息处理子系统及通信子系统.在此基础上,进行重载机械臂控制系统作业试验.试验结果表明,该控制系统能够完成人机交互作业功能,相对于传统重载机械臂作业手段,有效提高了作业效率70%,保障了作业人员安全,验证了所提出控制系统的人机友好性、可行性和实用性.     

基于专家PID的带臂四旋翼无人机控制方法

相较于未带臂的无人机,带臂无人机（UAV）的飞行轨迹会出现较大偏差,更难以稳定控制。为了解决带臂UAV的精确轨迹控制问题,提出基于专家PID的带臂四旋翼无人机控制方法。首先,将机械臂搭载于UAV上把它们作为整体,并通过拉格朗日方程建立了带臂UAV的运动学和动力学系统模型;其次,设计专家PID控制器用于对系统的稳定控制;然后利用五次多项式对带臂UAV的机械臂进行轨迹规划;最后,通过仿真验证专家PID控制方法对带臂UAV稳定控制的有效性。实验结果表明,相较于常规PID控制,所提基于专家PID的控制方法提高了系统的响应速度,且能够有效地抑制外部扰动;该方法对于动作情况下的机械臂能够稳定地跟踪其轨迹,且具有很好的抗扰性和鲁棒性。