Cooperative object manipulation with contact impact using multiple impedance control

Impedance Control imposes a desired behavior on a single manipulator interacting with its environment. The Multiple Impedance Control (MIC) enforces a designated impedance on both a manipulated object, and all cooperating manipulators. Similar to the standard impedance control, one of the benefits of this algorithm is the ability to perform both free motions and contact tasks without switching control modes. At the same time, the potentially large object inertia and other forces are taken into account. In this paper, the general formulation for the MIC algorithm is developed for distinct cooperating manipulators, and important issues are detailed. Using a benchmark system, the response of the MIC algorithm is compared to that of the Object Impedance Control (OIC). It is shown that in the presence of flexibility, the MIC algorithm results in an improved performance. Next, a system of two cooperating two-link manipulators is simulated, in which a Remote Centre Compliance is attached to the second end-effector. As simulation results show, the response of the MIC algorithm is smooth, even in the presence of an impact due to collision with an obstacle. It is revealed by both error analysis and simulation that under the MIC law, all participating manipulators, and the manipulated object exhibit the same designated impedance behavior. This guarantees good tracking of manipulators and the object based on the chosen impedance laws which describe desired error dynamics, in performing a manipulation task.     

Adaptive neural controller for cooperative multiple robot manipulator system manipulating a single rigid object

In this article, an adaptive neural controller is developed for cooperative multiple robot manipulator system carrying and manipulating a common rigid object. In coordinated manipulation of a single object using multiple robot manipulators simultaneous control of the object motion and the internal force exerted by manipulators on the object is required. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as the states of the derived model. Based on this model, a controller is proposed that achieves required trajectory tracking of the object as well as tracking of the desired internal forces arising in the system. A feedforward neural network is employed to learn the unknown dynamics of robot manipulators and the object. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary offline learning. The adaptive learning algorithm is derived from Lyapunov stability analysis so that both error convergence and tracking stability are guaranteed in the closed loop system. Finally, simulation studies and analysis are carried out for two three-link planar manipulators moving a circular disc on specified trajectory.     

A HUMANLIKE GRASPING FORCE PLANNER FOR OBJECT MANIPULATION BY ROBOT MANIPULATORS

Recently robot manipulators have been expected to perform sophisticated tasks such as object manipulation, assembly tasks, or cooperative tasks with human workers. In order to realize these tasks with robot manipulators, it is important to understand the human strategy of object grasping and manipulation. In this study, we have examined how a human being decides the grasping force necessary to manipulate an unknown object in order to apply human object-grasping strategy for robotic systems. Experiments have been performed with several kinds of objects under several kinds of conditions to investigate how much grasping force human subjects generate. Adjustment strategy of human grasping force when the object is manipulated or in contact with an environment is also examined. Neural networks (the desired grasping force planner) that generate the humanlike desired grasping force are then designed for robotic systems. The effectiveness of the proposed desired grasping force planner is evaluated via experiments.     

VARIABLE STRUCTURE CONTROL OF TWO MANIPULATORS HANDLING A CONSTRAINED OBJECT

The control of two manipulators handling a constrained object involves the control of the position of the object, the internal force used to grasp the object, and the constraint force due to the constraint surface. The robustness of the controller must be guaranteed when the system faces parameter uncertainties and or external disturbances. In this paper, a variable structure control law is proposed. This controller guarantees the asymptotic convergence of the position of the object, internal force, and constraint force to their desired values when uncertainties on the parameters and external disturbances are present in the system. Simulation results for two planar robots moving an object along a horizontal plane illustrate the fact that the proposed controller achieves the desired asymptotic tracking.     

On tracking control of cooperative hydraulic manipulators

This paper addresses the problem of tracking control of multiple hydraulic manipulators handling a rigid object. We propose a controller that allows two or more hydraulically-actuated robots cooperatively, to move a rigid object along a desired trajectory while sharing the load and maintaining an acceptable internal force on the object. The parasitic effect of friction in the actuators, as well as parametric uncertainties in the manipulators’ dynamics, hydraulic functions and the payload, are compensated through augmentation of the controller by a set of online updating laws. Additionally, an adaptive observer is used along with the controller to avoid the requirement of acceleration feedback, which could be difficult to obtain in practice. Only measurements of joint positions, joint velocities and hydraulic line pressures are required for the implementation of the controller. The tracking error of the control system is proven to converge to zero while the internal force remains bounded. It is further proven that the internal force can be set as close as possible to the desired value through the addition of a simple force feedback loop with an adjustable gain. Both simulation and experimental studies are conducted to clearly illustrate the effectiveness of the developed controller for various tracking tasks. The simulations are carried out using a complete nonlinear model of two multiple-degree-of-freedom industrial hydraulic manipulators handling a rigid object. Experiments are carried out on an available fully-instrumented electro-hydraulic system.     

Distributively controlling two robots handling an object in thetask space without any communication

Two distributed cooperation controllers are presented for trajectory tracking of two manipulators which are cooperatively handling an object. The controllers control the positions of the robots distributively by using the trajectory error of the object in the task space. In the first controller, the internal force between the object and a manipulator is controlled only by a feedforward of the desired force. The second controller uses a force feedback. No communication is required between the manipulators in both the controllers. Their globally and exponentially asymptotic stabilities are guaranteed by Lyapunov functions     

Robust Adaptive Control of Cooperating Mobile Manipulators With Relative Motion

In this paper, coupled dynamics are presented for two cooperating mobile robotic manipulators manipulating an object with relative motion in the presence of uncertainties and external disturbances. Centralized robust adaptive controls are introduced to guarantee the motion, and force trajectories of the constrained object converge to the desired manifolds with prescribed performance. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The tracking of the constraint trajectory/force up to an ultimately bounded error is achieved. The proposed adaptive controls are robust against relative motion disturbances and parametric uncertainties and are validated by simulation studies.     

On the robust control of two manipulators holding a rigid object

In this paper, a control architecture is developed for the closed chain motion of two six-joint manipulators holding a rigid object in a three-dimensional workspace. Dynamic and kinematic constraints are combined with the equations of motion of the manipulators to obtain a dynamical model of the entire system in the joint space. Reduced-order dynamic equations are then developed with regard to the position and force control variables. Robust control laws are then determined such that the force and position control design is decoupled. The control laws that will be discussed are: a robust position tracking controller that yields an exponentially stable position tracking error result, and a robust force tracking controller that yields adjustable bounds on the force tracking error.     

Direct adaptive impedance control of robot manipulators

This article presents an adaptive scheme for controlling the end-effector impedance of robot manipulators. The proposed control system consists of three subsystems: a simple “filter” that characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller that produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter. Computer simulation results are given for a planar four degree-of-freedom redundant robot under adaptive impedance control. These results demonstrate that accurate end-effector impedance control and effective redundancy utilization can be achieved simultaneously by using the proposed controller.     

Position and Force Control of Two Constrained Robotic Manipulators

In this paper, the problem of controlling two robotic manipulators handling a constrained object is addressed. First, a reduced order dynamic model of the system is obtained. Using this model, a controller that guarantees the asymptotic convergence of the position, the internal force, and the constraint force to their desired values is proposed. Simulation results for two three-link planar manipulators moving a constrained object demonstrate the effectiveness of the proposed controller.     

考虑柔性关节的机械臂自适应运动控制策略研究

具有柔性关节的轻型机械臂因其自重轻、响应迅速、操作灵活等优点,取得了广泛应用;针对具有柔性关节的机械臂系统的关节空间轨迹跟踪控制系统动力学参数不精确的问题,提出一种结合滑模变结构设计的自适应控制器算法;通过自适应控制的思想对系统动力学参数进行在线辨识,并采用Lyapunov方法证明了闭环系统的稳定性;仿真结果表明,该控制策略保证了机械臂系统对期望轨迹的快速跟踪,具有良好的跟踪精度,系统具有稳定性。     

参数未知的多个操作器的一种自适应控制算法

在多个操作器的内力与运动的控制中,内力控制是主要的挑战.在假设接触模型为点接触的前提下,讨论了参数未知的多个操作器内力的自适应控制.先给出多个操作器所成系统具有的一些特性;其次导出了内力误差与动力学参数间的关系;最后在条件PE(persistent-exciting)不成立的情况下,给出了一种保证内力收敛于零的复合控制.由理论证明及仿真实验可知,本文给出的控制器既使被操作的物体运动轨迹渐进跟踪期望的运动轨迹,又使作用在物体上的内力渐进跟踪期望的内力.     

Motion/force control scheme for electrically driven cooperative multiple mobile manipulators

This paper presents the motion and force control problem of rigid-link electrically driven cooperative mobile manipulators handling a rigid object. Although, the motion/force control problem of cooperative mobile manipulators has been enthusiastically studied. But there is little research on the motion/force control of electrically driven cooperative mobile manipulators. Due to the inclusion of the actuator dynamics with the manipulator’s dynamics, the controller exhibits some important characteristics. For the electromechanical system, we have designed a novel controller at the dynamic level as well as at the actuator level. In the proposed control scheme, at the dynamic level, uncertain non-linear mechanical dynamics is approximated with a hybrid controller containing model-based control scheme combined with model-free neural network based control scheme together with an adaptive bound. The adaptive bound is used to suppress the effects of external disturbances, friction terms, and reconstruction error of the neural network. At the actuator level, for the approximation of the unknown electrical dynamics, the model-free neural network is utilized. The developed control scheme provides that the position tracking errors, as well as the internal force, converge to the desired levels. Additionally, direct current motors are also controlled in such a way that the desired currents and torques can be attained. In order to make the overall system to be asymptotically stable, online learning of the weights and the parameter adaptation of the parameters is utilized in the Lyapunov function. The superiority of the developed control method is carried out with the numerical simulation results and its superior robustness is shown in a comparative manner.     

基于超宽带技术的运动目标跟踪高精度定位系统设计

为克服运动目标不断变化导致跟踪定位精度较低的问题,设计基于超宽带技术的运动目标跟踪高精度定位系统;图像采集模块由FPGA单元、VGA显示单元、帧缓存单元以及图像采集单元构成,以此实现运动目标跟踪与定位中的图像采集,在超宽带技术模块中,设计超宽带运动目标定位所需的天线、定位基站、移动节点,完成超宽带动态组网,实现硬件系统的设计;基于硬件系统采集到的图像,实施图像灰度化处理、形态学滤波处理,以增强图像中有用的信息,设计TLD运动目标跟踪算法,随着运动目标开始运动,TLD模型会不断学习跟踪的运动目标,获取目标在距离、景深、角度等层面的改变,并不断学习、识别,达到良好的跟踪效果,基于超宽带技术设计运动目标动态定位算法,依据跟踪结果实现运动目标的高精度定位,完成软件系统的设计;实验测试结果表明,该系统在中、远距离目标跟踪与定位实验中跟踪错误率低于0.60%、2.4%,沿着S型运动时,路线弯折处的定位误差较低,与实验运动目标的飞行路线相贴合,具有良好的定位能力。     

Model-free Adaptive Dynamic Programming Based Near-optimal Decentralized Tracking Control of Reconfigurable Manipulators

In this paper, a model-free near-optimal decentralized tracking control (DTC) scheme is developed for reconfigurable manipulators via adaptive dynamic programming algorithm. The proposed controller can be divided into two parts, namely local desired controller and local tracking error controller. In order to remove the normboundedness assumption of interconnections, desired states of coupled subsystems are employed to substitute their actual states. Using the local input/output data, the unknown subsystem dynamics of reconfigurable manipulators can be identified by constructing local neural network (NN) identifiers. With the help of the identified dynamics, the local desired control can be derived directly with corresponding desired states. Then, for tracking error subsystems, the local tracking error control is investigated by the approximate improved local cost function via local critic NN and the identified input gain matrix. To overcome the overall error caused by the substitution, identification and critic NN approximation, a robust compensation is added to construct the improved local cost function that reflects the overall error, regulation and control simultaneously. Therefore, the closed-loop tracking system can be guaranteed to be asymptotically stable via Lyapunov stability theorem. Two 2-degree of freedom reconfigurable manipulators with different configurations are employed to demonstrate the effectiveness of the proposed modelfree near-optimal DTC scheme.     

基于视频分析的智能监控系统

智能监控是当前计算机视觉研究的热点领域之一。针对室内监控的具体特点,实现了一种基于视频分析的智能检测跟踪监控系统。利用基于统计模型的目标检测算法提取运动目标;然后结合Meanshift算法对目标进行粗跟踪;最后针对Meanshift算法无法实时改变跟踪窗大小的缺陷,提出边界力调整算法以自适应更新跟踪窗窗宽。并以DM642数字图像处理DSP为核心,设计并搭建了智能视频监控平台。实验表明,该系统可以实时有效地检测、跟踪室内运动目标。     

轮式移动机械臂的鲁棒跟踪控制研究

移动机械臂系统一般由移动平台和机器臂组成,它既具有机器臂的操作灵活性,又具有移动机器人的可移动性,因此其应用范围要比单个系统宽得多。这篇文章研究了由非完整移动平台和完整机械臂构成的移动机械臂系统的鲁棒跟踪控制问题,基于误差动态方程和耗散不等式引理设计了一种鲁棒跟踪控制器,该控制器在出现外界干扰时能使系统渐近跟踪给定信号。使用Matlab6.5对系统进行了仿真研究,仿真结果表明所提出的鲁棒控制算法是正确有效的。     

一种机器人自适应阻抗控制算法

本文针对参数未知及负载不确定下的机器人运动控制问题，提出了一种形式非常简洁的自适应阻抗控制算法，它能使机器人系统跟踪目标阻抗并保证跟踪误差的渐近稳定性及机器人与外界整体系统的稳定性，本文还就无直接力反馈控制方法进行了讨论。     

Dynamics and Cooperative Object Manipulation Control of Suspended Mobile Manipulators

Dynamics and control of mobile manipulators is obviously a more challenging problem compared to fixed-base robots. Including a suspension system for these mobile platforms increases their maneuverability, but considerably adds to their complexity. In this paper, a suspended wheeled mobile platform with two 6-DOF Puma-type manipulators is used to manipulate an object along a given path. To apply a model-based control algorithm, it is required to have an explicit dynamics model for such highly nonlinear system. This model should be as concise as possible to include fewer mathematical calculations for online computations. Therefore in this paper, a detailed set of dynamics equations for a multiple arm wheeled mobile platform equipped with an effective suspension system is presented. The method is based on the concept of Direct Path Method (DPM), which is extended here for such challenging type of robots. The obtained dynamics model is then verified with a dynamical analysis study using software ADAMS. Then, Natural Orthogonal Complement Method is used to include the non-holonomic constraint of the wheeled platform in a more concise dynamics model. Next, an impedance control law is applied for cooperative manipulation of an object by the two manipulators. The obtained results for a suspended wheeled platform equipped with two 6-DOF Puma-type manipulators reveal a successful performance for moving an object along a mixed circular-straight path, even in the presence of unexpected disturbing forces, system/end-effector flexibility and impacts due to contact with an obstacle.     

改进的高效Camshift跟踪算法

Camshift是一种应用颜色信息的跟踪算法,它对做加速度的运动物体跟踪效果不够稳定和强壮,从准确预测目标位置及缩小目标搜索范围入手对Camshift算法进行了改进。该算法使用运动目标加速度运动位移方程预测下一时刻目标可能出现的位置,使用预测位置误差方程估计运动目标搜索范围,并使用IIR滤波器对目标运动速度、加速度等参数自适应地修正。实验证明,改进的Camshift有效地克服了Camshift算法自身的缺陷,即使运动目标做加速运动时,也可准确地预测运动目标的位置,缩小目标搜索范围,进而提高目标跟踪速度。