不确定非完整移动机器人的轨迹跟踪控制

具有未校准视觉参数的非完整移动机器人的运动学系统具有参数不确定性,较一般的运动学系统更加复杂.基于视觉反馈、Barbalat's定理和Lyapunov直接方法,研究了具有未标定摄像机参数的非完整移动机器人的轨迹跟踪问题.首先,利用固定在天花板上的针孔摄像机透视投影模型,提出了一种新的基于视觉伺服的移动机器人运动学跟踪误差模型;基于这个模型,提出了一种新的与未知视觉参数无关的动态反馈跟踪控制器.该控制器不仅保证系统的状态渐近跟踪给定参考轨迹,而且控制器是全局的,通过Lyapunov方法严格证明了闭环系统的稳定性.在惯性系和图像坐标系下讨论跟踪问题,使问题变的简单且设计的控制器更加有用.最后,仿真结果证实了所提出的控制器的有效性.     

具有未知视觉参数的非完整移动机器人的自适应动态反馈跟踪控制

基于视觉反馈和标准链式形式,研究了一类不确定非完整移动机器人的轨迹跟踪控制问题.首先,利用针孔摄像机模型,提出了一种新的基于视觉伺服的移动机器人运动学跟踪误差模型.基于这个模型,在具有不确定视觉参数的情形下,利用back-stepping技术,设计出了一种新的自适应动态反馈跟踪控制器,实现了全局渐近的轨迹跟踪,并通过李亚普诺夫方法严格证明了闭环系统的稳定性和估计参数的有界性.仿真结果证明了所提出的控制器的有效性.     

An anthropomorphic controlled hand prosthesis system

Based on HIT/DLR(Harbin Institute of Technology/Deutsches Zentrum für Luft-und Raumfahrt) Prosthetic Hand II,an anthropomorphic controller is developed to help the amputees use and perceive the prosthetic hands more like people with normal physiological hands.The core of the anthropomorphic controller is a hierarchical control system.It is composed of a top controller and a low level controller.The top controller has been designed both to interpret the amputee’s intensions through electromyography(EMG) signals recognition and to provide the subject-prosthesis interface control with electro-cutaneous sensory feedback(ESF),while the low level controller is responsible for grasp stability.The control strategies include the EMG control strategy,EMG and ESF closed loop control strategy,and voice control strategy.Through EMG signal recognition,10 types of hand postures are recognized based on support vector machine(SVM).An anthropomorphic closed loop system is constructed to include the customer,sensory feedback system,EMG control system,and the prosthetic hand,so as to help the amputee perform a more successful EMG grasp.Experimental results suggest that the anthropomorphic controller can be used for multi-posture recognition,and that grasp with ESF is a cognitive dual process with visual and sensory feedback.This process while outperforming the visual feedback process provides the concept of grasp force magnitude during manipulation of objects.     

不校准视觉参数的非完整运动学系统的鲁棒指数镇定

基于视觉反馈和非完整（1,2）型移动机器人的标准链式形式,探讨了具有不校准视觉参数的机器人的鲁棒镇定问题,得到了这种机器人在图像平面内新的非完整运动学系统的不确定链式模型.借助于状态缩放和切换技术,对非完整不确定链式模型提出了新的指数镇定的时变反馈控制器,并给出了指数镇定的严格证明.仿真结果验证了控制器设计的有效性.     

Robust exponential stabilization of nonholonomic wheeled mobile robots with unknown visual parameters

The visual servoing stabilization of nonholonomic mobile robot with unknown camera parameters is investigated.A new kind of uncertain chained model of nonholonomic kinemetic system is obtained based on the visual feedback and the standard chained form of type (1,2) mobile robot.Then,a novel time-varying feedback controller is proposed for exponentially stabilizing the position and orientation of the robot using visual feedback and switching strategy when the camera parameters are not known.The exponential stability of the closed-loop system is rigorously proven.Simulation results demonstrate the effectiveness of the method proposed in this paper.     

Visual tracking control for an uncalibrated robot system with unknown camera parameters

The robust trajectory tracking problem for an eye-in-hand system is addressed in this paper. A novel visual feedback control model is proposed. It considers not only the uncertainties and disturbances in the robot model, but also the unknown camera parameters. By using sliding mode control, filter method and adaptive technique, the controller is designed such that the robot can track the desired trajectory well by using information provided by camera. Finally, stability and robustness are rigorously proved by using Lyapunov method. Computer simulations are presented to show the effectiveness of the proposed visual feedback controller.     

CPG modulation for navigation and omnidirectional quadruped locomotion

Navigation in biological mechanisms represents a set of skills needed for the survival of individuals, including target acquisition and obstacle avoidance.In this article, we focus on the development of a quadruped locomotion controller able to generate omnidirectional locomotion and a path planning controller for heading direction. The heading direction controller is able to adapt to sensory-motor visual feedback, and online adapt its trajectory according to visual information that modifies the control parameters. This allows for integration of sensory-motor feedback and closed-loop control. This issue is crucial for autonomous and adaptive control, and has received little attention so far. This modeling is based on the concept of dynamical systems.We present experiments performed on a real AIBO platform. The obtained results demonstrate both the adequacy of the proposed locomotor controller to generate the required trajectories and to generate the desired movement in terms of the walking velocity, orientation and angular velocity. Further, the controller is demonstrated on a simulated quadruped robot which walks towards a visually acquired target while avoiding online-visually detected obstacles in its path.     

机器人视觉伺服中CMAC学习控制系统研究

根据小脑模型关联控制器（CMAC）收敛速度快,适于实时控制系统的特点,设计了一种基于CMAC学习控制方法的机器人视觉伺服系统。在该系统中,CMAC被用作前馈视觉控制器对常规反馈控制器进行补偿。所提出的CMAC控制器替代图像雅可比矩阵来获得目标图像特征和机器人关节运动之间2D/3D变换关系,通过其在线学习,可以使系统对摄像机标定误差不敏感,从而提高系统的鲁棒性。实验证明了所设计控制系统的有效性。     

A Modular Scheme for Controller Design and Performance Evaluation in 3D Visual Servoing

In this paper we present a modular scheme for designing and evaluating different control systems for position based dynamic look and move visual servoing systems. This scheme is particularly applied to a 6 DOF industrial manipulator equipped with a camera mounted on its end effector. The manipulator with its actuators and its current feedback loops can be modeled as a Cartesian device commanded through a serial line. In this case the manipulator can be considered as a decoupled system with 6 independent loops. The use of computer vision as feedback transducer strongly affects the closed loop dynamics of the overall system, so that a visual controller is required for achieving fast response and high control accuracy. Due to the long delay in generating the control signal, it is necessary to carefully select the visual controller. In this paper we present a framework that allows the study of some conventional and new techniques to design this visual controller. Besides an experimental setup has been built and used to evaluate and compare the performance of the position based dynamic look and move system with different controllers. Some criterions for selecting the best strategy for each task are established. Quite a lot of results relative to different trajectory tracking control strategies are presented, showing both simulation and real platform responses.     

Bounded‐Input Control of the Quadrotor Unmanned Aerial Vehicle: A Vision‐Based Approach

In this paper, a bounded‐input controller is designed for the quadrotor vertical take‐off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image‐based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a bounded‐input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.     

Attitude estimation and control of a 3-DOF lab helicopter only based on optical flow

This paper proposes an attitude estimation method based on optical flow to solve the attitude tracking control problem for a three degree-of-freedom (3-DOF) lab helicopter. First, the relationship between optical flow and the motion of a general unmanned aerial vehicle is derived from the transformation between the image coordinate frame and the world coordinate frame. Then, an expression for the angular velocity of the 3-DOF helicopter is deduced only based on optical flow, and the attitude information is acquired by solving nonlinear equations. Finally, using visual feedback, a linear quadratic regulation (LQR) controller is designed for hovering and tracking, which consists of a feedforward controller and a LQR state feedback controller. Closed-loop experimental results on the lab helicopter demonstrate the effectiveness of the proposed estimation and control methods.     

Dynamic feedback robust stabilization of nonholonomic mobile robots based on visual servoing

This paper investigates the visual servoing robust stabilization of nonholonomic mobile robots. The calibration of visual parameters is not only complicated, but also needs great consumption of calculated time so that the accurate calibration is impossible in some situations for high requirement of real timing. Hence, it is interesting and important to consider the design of stabilizing controllers for nonholonomic kinematic systems with uncalibrated visual parameters. A novel uncertain model of these nonholonomic kinematic systems is proposed. Based on this model, a stabilizing controller is discussed by using dynamic feedback and two-step techniques. The proposed robust controller makes the mobile robot image pose and the orientation converge to the desired configuration despite the lack of depth information and the lack of precise visual parameters. The stability of the closed loop system is rigorously proved. The simulation is given to show the effectiveness of the presented controllers.     

一类非线性系统的神经网络控制器建模方法及其仿真研究

该文基于反馈线性化的思想，研究了一类非线性系统的神经网络控制器的建模方法，并以倒立摆控制系统为例，在Matlab环境下进行了仿真实验。仿真结果表明，该文所讨论的方法有效可行，使非线性系统具有较好的跟踪性能，为反馈线性化控制技术在实际的非线性系统中的应用创造了条件。     

Adaptive tracking control for uncertain dynamic nonholonomic mobile robots based on visual servoing

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback. A kinematic controller is firstly presented for the kinematic model, and then, an adaptive sliding mode controller is designed for the uncertain dynamic model in the presence of parametric uncertainties associated with the camera system. The proposed controller is robust not only to structured uncertainties such as mass variation but also to unstructured one such as disturbances. The asymptotic convergence of tracking errors to equilibrium point is rigorously proved by the Lyapunov method. Simulation results are provided to illustrate the performance of the control law.     

Adaptive tracking control for uncertain dynamic nonholonomic mobile robots based on visual servoing

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback.A kinematic controller is firstly presented for the kinematic model,and ...     

Balancing control of a bicycle-riding humanoid robot with center of gravity estimation

In this research, a miniaturized humanoid robot is constructed to ride and pedal a bicycle of comparable size. The design of the controller for the robot to balance and steer the bicycle using the handlebar is of particular interest. The controller possesses the capability to estimate the uncertain center of gravity of the robot-bicycle system and then incorporate such an estimation to enhance control performance. A general control framework which can achieve asymptotic stability under uncertain measurement biases is adopted for controller design. Using the framework, the stability of the control system is analytically guaranteed and its control parameters can be determined in a systematic manner. Both simulations and experiments verify that the proposed controller can automatically counteract the mass imbalance in the robot-bicycle system and allow it to perform straight-line steering without using camera visual feedback.     

State and mode feedback control strategy for discrete‐time Markovian jump linear systems with time‐varying controllable mode transition probability matrix

In this article, the state and mode feedback control strategy is investigated for the discrete‐time Markovian jump linear system (MJLS) with time‐varying controllable mode transition probability matrix (MTPM). This strategy, consisting of a state feedback controller and a mode feedback controller, is proposed to ensure MJLS's stability and meanwhile improve system performance. First, a mode‐dependent state feedback controller is designed to stabilize the MJLS based on the time‐invariant part of the MTPM such that it can still keep valid even if the MTPM is adjusted by the mode feedback control. Second, a generalized quadratic stabilization cost is put forward for evaluating MJLS's performance, which contains system state, state feedback controller, and mode feedback controller. To reduce the stabilization cost, a mode feedback controller is introduced to adjust each mode's occurrence probability by changing the time‐varying controllable part of MTPM. The calculation of such mode feedback controller is given based on a value‐iteration algorithm with its convergence proof. Compared with traditional state feedback control strategy, this state and mode feedback control strategy offers a new perspective for the control problem of general nonhomogeneous MJLSs. Numerical examples are provided to illustrate the validity of the proposed strategy.     

Vision Based Output Feedback Control of Micro Aerial Vehicles in Indoor Environments

We present a new image based visual servoing (IBVS) approach for control of micro aerial vehicles (MAVs) in indoor environments. Specifically, we show how a MAV can be stabilized and guided using only corridor lines viewed on a front facing camera and angular velocity measurements. Since the suggested controller does not include explicit attitude feedback it does not require the use of accelerometers which are susceptible to vibrations, nor complex attitude estimation algorithms. The controller also does not require direct velocity measurements which are difficult to obtain in indoor environments. The paper presents the new method, stability analysis, simulations and experiments.     

基于神经网络的一类非线性系统自适应输出跟踪

针对一类未知非线性系统,提出了一种输出反馈控制方法.首先,在假设系统状态已 知情况下设计状态反馈控制器,实现跟踪性能;然后,在系统状态不完全可测的情况下,通过 设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计,证明了所设计的输出 反馈控制器可以获得状态反馈控制器的性能.     

电子纸显示控制器S1D13521的人机交互设计

新型电子纸显示控制器SID13521的推出,为提升电子纸显示屏人机界面体验带来了强大技术支持。结合SID13521诸多新特性,本文建立一种控制一反馈人机交互结构模型,在此基础上设计了电子纸人机交互基本操控手势及界面布局,并通过动态视觉反馈设计提升交互体验。经在津科V30型手持阅读器上验证,该设计简便易行、效果良好。