基于六维力传感器的工业机器人末端负载受力感知研究

针对工业机器人末端负载与外界环境接触力的感知需求,在机器人法兰与负载之间设置六维力传感器,并研究一套标定与计算方法,综合考虑负载重力作用、传感器零点、机器人安装倾角等因素,利用不少于3个机器人姿态下的力传感器数据,可求得传感器零点、机器人安装倾角、负载重力大小、负载重心坐标等参数,进一步可消除传感器零点及负载重力对受力感知的影响,精确得到机器人末端负载所受的外部作用力与力矩.实验得到对于重量从320N到1917N的负载,在静态条件下,感知外力的误差在负载重力的0.28%以内,感知外力矩的误差在负载对传感器力矩的0.59%以内.     

Human direct teaching of industrial articulated robot arms based on force-free control

Force-free control produces motion in a robot arm as if it were under conditions with no gravity and no friction. In this study, a method of force-free control is proposed for industrial articulated robot arms. The force-free control proposed was applied to the direct teaching of industrial articulated robot arms in that the robot arm was moved by direct human force. Generally, the teaching of industrial articulated robot arms is carried out using operational equipment called a teach-pendant. Smooth teaching can be achieved if direct teaching is applicable. The force-free control proposed enables humans to teach industrial articulated robot arms directly. The effectiveness of force-free control was confirmed by experimental work on an articulated robot arm with two degrees of freedom. This work was presented in part at the Fifth International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

Position-based force tracking adaptive impedance control strategy for robot grinding complex surfaces system

As a key technology of robot grinding, force control has great influence on grinding effects. Based on the traditional impedance control, a position-based force tracking adaptive impedance control strategy is proposed to improve the grinding quality of aeroengine complex curved parts, which considers the stiffness damping environmental interaction model, modifies the reference trajectory by a Lyapunov-based approach to realize the adaptive grinding process. In addition, forgotten Kalman filter based on six-dimensional force sensor is used to denoise the force information and a three-step gravity compensation process including static base value calculation, dynamic zero update and contact force real-time calculation is proposed to obtain the accurate contact force between tool and workpiece in this method. Then, to verify the effectiveness of the proposed method, a simulation experiment which including five different working conditions is conducted in MATLAB, and the experiment studying the deviation between the reference trajectory and the actual position is carried out on the robot grinding system. The results indicate that the position-based force tracking adaptive impedance control strategy can quickly respond to the changes of environmental position, reduce the fluctuation range of contact force in time by modifying the reference trajectory, compensate for the defect of the steady-state error of the traditional impedance control strategy and improve the surface consistency of machined parts.     

Independent traction control for uneven terrain using stick-slip phenomenon: application to a stair climbing robot

Mobile robots are being developed for building inspection and security, military reconnaissance, and planetary exploration. In such applications, the robot is expected to encounter rough terrain. In rough terrain, it is important for mobile robots to maintain adequate traction as excessive wheel slip causes the robot to lose mobility or even be trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The algorithm estimates the stick-slip of the wheels based on estimation of angular acceleration. Thus, the traction force induced by torque of wheel converses between the maximum static friction and kinetic friction. Simulations and experiments are performed to validate the algorithm. The proposed traction control algorithm yielded a 40.5% reduction of total slip distance and 25.6% reduction of power consumption compared with the standard velocity control method. Furthermore, the algorithm does not require a complex wheel-soil interaction model or optimization of robot kinematics.     

Friction modeling and compensation for an industrial robot

This article describes the detailed friction modeling of the General Electric GP132 industrial robot. Friction is an area whose importance is often discounted in the development of control systems because it is thought to be insignificant or unmodelable. This work demonstrates that friction does have a predictable structure, and that significant performance improvement can be realized through its proper compensation. Experiments performed to determine the static, Coulomb, and viscous friction of the GP132 are presented. In addition to these components, the robot is shown to have significant gravity load-dependent and position-dependent friction. The accuracy of the friction models are verified through several experiments and are shown to be considerably better than previously formulated models.     

基于数据挖掘与系统理论建立摩擦模糊模型与控制补偿

建立机械摩擦力模型及其相应的控制补偿策略一直是人们所关注的问题. 由于摩擦力所固有的非线性及不确定特征, 用传统的数学建模与控制补偿方法难以达到满意的系统性能要求. 本文采用模糊建模技术逼近摩擦动力系统并将辨识结果用在前馈补偿控制器设计中. 模糊建模过程由以下3个部分组成: 首先采用数据挖掘技术辨识出模糊系统的模糊规则库, 然后利用该规则库建立模糊系统的静态模型, 最后以李雅普诺夫稳定性理论为基础进一步辨识出模糊系统的动态模型. 在控制器设计方面, 采用了自适应模糊系统前馈补偿的比例微分(Proportional-derivative, PD)算法. 运用李雅普诺夫稳定性分析证明了闭环系统跟踪误差的有界性. 数值仿真结果表明了该方法的有效性和实用性.     

对未知环境的机器人力控自律跟踪及建模

在考虑摩擦力的情况下，利用传感器所感知的机器人和未知轮廓间的相互作用力确接触处轮廓的切矢和法矢，据此建立端点约束坐标系，在该坐标系中沿切矢进行位置控制并沿法矢进行力控制。实现机器人对未知轮廓的自律跟踪运动。由跟踪运动所确定每一点处切矢信息及该点位置信息构造未知轮廓几何模型。在机器人学开放研究实验室的ＰＵＭＡ５６２机器人上实现了上述自律运动并建立了环境模型。     

PD control with on-line gravity compensation for robots with elastic joints: Theory and experiments

A proportional-derivative (PD) control with on-line gravity compensation is proposed for regulation tasks of robot manipulators with elastic joints. The work extends a previous PD control with constant gravity compensation at the desired configuration. The control law requires measuring only position and velocity on the motor side of the elastic joints, while the on-line gravity compensation torque uses a biased measure of the motor position. It is proved via a Lyapunov argument that the control law globally asymptotically stabilizes the desired robot configuration. A simulation study on a two-joint arm reveals the better performance that can be obtained with the new scheme as compared to the case of constant gravity compensation. Moreover, the proposed controller is experimentally tested on an eight-joint cable-driven robot manipulator, in combination with a point-to-point interpolating trajectory, showing the practical advantages of the on-line compensation.     

Shadow robot for teaching motion

Human-friendly robots have begun to spread in society. In the future such robots and intelligent machines should be autonomous in open situations. To give dexterity to a robot, teaching motion is a good candidate. However, there are some problems from the operational point of view due to gravity and friction effects.In this paper, a shadow robot is proposed for teaching motion instead of force sensors. The shadow robot is a novel disturbance compensation method that consists of a twin robot system. Two of the same type of robot are required and they are controlled with the same position, velocity, and acceleration by bilateral acceleration control based on a disturbance observer. One robot is in the teaching motion controlled by a human and the other is unconstrained. Thus the purity of the human force is extracted by subtracting the disturbance torque in the unconstrained robot from the constrained one. As a result, the shadow robot observes the human force with gravity and friction compensation. Since it is possible to apply this concept to a multi-degree-of-freedom system, the human operationality in teaching motion are improved.The experimental results show the viability of the proposed method.     

Development and Evaluation of a 7-DOF Haptic Interface

With the development of human robot interaction technologies, haptic interfaces are widely used for 3D applications to provide the sense of touch. These interfaces have been utilized in medical simulation, virtual assembly and remote manipulation tasks. However, haptic interface design and control are still critical problems to reproduce the highly sensitive touch sense of humans. This paper presents the development and evaluation of a 7-DOF (degree of freedom) haptic interface based on the modified delta mechanism. Firstly, both kinematics and dynamics of the modified mechanism are analyzed and presented. A novel gravity compensation algorithm based on the physical model is proposed and validated in simulation. A haptic controller is proposed based on the forward kinematics and the gravity compensation algorithm. To evaluate the control performance of the haptic interface, a prototype has been implemented. Three kinds of experiments:gravity compensation, static response and force tracking are performed respectively. The experimental results show that the mean error of the gravity compensation is less than 0.7 N and the maximum continuous force along the axis can be up to 6 N. This demonstrates the good performance of the proposed haptic interface.      

利用BP-NN算法的机器人臂重力补偿研究

利用反向传播神经网络(BP-NN)学习算法,对机器人臂的重力补偿进行了研究。给出了机器人臂各关节扭矩的重力项理论计算公式及其连杆参数识别方法,同时,对BP-NN算法进行了详细分析,利用BP-NN来处理机器人臂重力项并进行试验。试验结果表明,采用该学习算法得到的机器人臂重力项输出值和实测值基本一致,能有效减少机器人臂重力项计算量,达到实时控制的目的。     

Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty

This study is devoted to sensorless adaptive force/position control of robot manipulators using a position-based adaptive force estimator (AFE) and a force-based adaptive environment compliance estimator. Unlike the other sensorless method in force control that uses disturbance observer and needs an accurate model of the manipulator, in this method, the unknown parameters of the robot can be estimated along with the force control. Even more, the environment compliance can be estimated simultaneously to achieve tracking force control. In fact, this study deals with three challenging problems: No force sensor is used, environment stiffness is unknown, and some parametric uncertainties exist in the robot model. A theorem offers control laws and updating laws for two control loops. In the inner loop, AFE estimates the exerted force, and then, the force control law in the outer loop modifies the desired trajectory of the manipulator for the adaptive tracking loop. Besides, an updating law updates the estimated compliance to provide an accurate tracking force control. Some experimental results of a PHANToM Premium robot are provided to validate the proposed scheme. In addition, some simulations are presented that verify the performance of the controller for different situations in interaction.     

Forcefree control with independent compensation for industrial articulated robot arms

Forcefree control of robot manipulators so far has been the passive motion of the arm due to the influence of external force under ideal conditions of zero gravity and zero friction, whereas this paper demonstrates forcefree control under assigned friction, gravity and inertia. The effectiveness of the proposed forcefree control with independent compensation is confirmed by comparing the experimental results with simulation results. Comparisons of the forcefree control with independent compensation to the other force control methods are also presented.     

Joint-space orthogonalization and passivity for physical interpretations of dextrous robot motions under geometric constraints

A principle of ‘joint-space orthogonalization’ is proposed as an extended notion of hybrid (force and position) control for robot manipulators under geometric constraints. The principle realizes the hybrid control in a strict sense by letting position feedback signals be orthogonal in joint space to the contact force vector whose components exert at corresponding joints. This orthogonalization is executed via a projection matrix computed in real-time from a Jacobian matrix of the constraint equation in joint coordinates. To show the important role of the principle in control of robot manipulators, two basic set-point control problems are analysed. One is a hybrid PID control problem for robot manipulators under geometric endpoint constraint and another is a coordinated control problem of two arms. It is shown that passivity properties of residual dynamics of robots follow from the introduction of a quasi-natural potential and the joint-space orthogonalization. Various stability problems of PID-type feedback control schemes without compensating for the gravity force and with or without use of a force sensor are discussed from passivity properties of robot dynamics with the aid of the hyper-stability theory.     

A sliding-mode based smooth adaptive robust controller for friction compensation

In this paper, a new approach employing both adaptive and robust methodologies is proposed for stick–slip friction compensation for tracking control of a one degree-of-freedom DC-motor system. It is well known that the major components of friction are Coulomb force, viscous force, exponential force (used to model the downward bend of friction at low velocity) and position-dependent force. Viscous force is linear and Coulomb force is linear in parameter; thus, these two forces can be compensated for by adaptive feedforward cancellation. Meanwhile, the latter two forces, which are neither linear nor linear in parameters, can only be partially compensated for by adaptive feedforward cancellation. Therefore, a robust compensator with an embedded adaptive law to ‘learn’ the upper bounding function on-line is proposed to compensate the uncancelled exponential and position-dependent friction. Lyapunov's direct method is utilized to prove the globally asymptotic stability of the servo-system under the proposed friction compensation method. Numerical simulations are presented as illustrations. © 1998 John Wiley & Sons, Ltd.     

基于连杆力矩传感器动态补偿的机器人灵巧手笛卡儿阻抗控制

为了对连杆空间力矩传感器进行动态补偿,提出了适用于求取串联机器人任意连杆中任意一点处所受的内力和内力矩的算法.该算法采用连杆假想截断原理利用牛顿-欧拉方程推导而出.推导过程综合考虑了串联机器人是否处于静态以及末端是否受外力作用的情况,以及串联机器人的关节是否是回转关节的情况.然后利用该算法计算动态补偿值,构建了基于连杆力矩传感器动态补偿的笛卡儿阻抗控制器.最后在HIT/DLR Hand II五指灵巧手上进行了实验验证.实验结果一方面验证了该算法的有效性,另一方面也验证了本文所构建的笛卡儿阻抗控制器的有效性.     

Effect of gravity on the static behavior of manipulators

The gravity-induced forces on revolute robot links dominate over the dynamic induced forces, particularly at low speeds. These forces, however, are generally ignored in conceptual analysis works due to the ensuing simplifications that their omission bring about. The force ellipsoid, the dynamic manipulability ellipsoid, and the generalized ellipsoid of inertia introduced by some researchers are but a few examples. For robot-arm control applications, the effect of gravity is usually isolated from the dynamic equations and then compensated for by the robot controller.This study presents a method to introduce the effect of gravity in the static analysis of robot arms. Using the concept of fields, the gravity-induced forces acting on individual links are replaced by a single force, called here the generalized weight of the arm. The generalized weight is a force that acts at the endpoint, and its magnitude and direction are functions of the configuration of the robot arm. The generalized weight field is then integrated with the force ellipsoid to result in the true force that a manipulator can apply to its environment. Since the system is conservative, the generalized weight is considered to be the gradient of a potential field called the generalized potential field. This field alone can illustrate the overall effect of gravity on the manipulator throughout its work volume.     

A Hybrid Intelligent Active Force Controller for Articulated Robot Arms Using Dynamic Structure Neural Network

The key feature of this paper is the application of a robotic control concept – Active Force Control (AFC). In this type of control, the unknown friction effect of the robotic arm may be compensated by the AFC method. AFC involves the direct measurement of the acceleration and force quantities and therefore, the process of estimating the system disturbance due to friction becomes instantaneous and purely algebraic. However, the AFC strategy is very practical provided a good estimation of the inertia matrix of articulated robot arm is acquired. A dynamic structure neural network – Growing Multi-experts Network (GMN) is developed to estimate the robot inertia matrix. The growing and pruning mechanism of GMN ensures the optimum size of the network that results in an excellent generalization capability of the network. Active Force Control (AFC) in conjunction with GMN successfully reduces the velocity and position tracking errors in spite of robot joint friction. The embedded GMN is capable of coupling the inertia matrix estimation on-line that clearly enhances the performance of AFC controller. The robustness and effectiveness of the new hybrid neural network-based AFC scheme are demonstrated clearly with regard to two link articulated robot and a simulated two-degree of freedom Puma 560 robot.     

Open-loop Velocity Control of Concrete Floor Finishing Robots

The twin trowel concrete floor finishing robot consists of a pair of trowels, each of which rotates four plastering blades, and does not have any mechanism like wheels for its locomotion. However, while leveling the concrete floor, it can move in any direction with the unbalanced friction forces occurring between the trowels and the floor, which are controlled by adjusting the posture of the trowels. For the motion control of the robot, this paper discusses the following: First, the typical velocity feedback control method is not dependable because of the difficulties of measuring the robot velocity; secondly, the friction force, which drives the robot, is modeled when the robot is in translation motion; thirdly, the friction force decreases as the robot velocity increases, thus resulting in a saturated velocity dependent on the posture of the trowel; finally, the saturated velocity enables us to control the motion of the robot only by adjusting the posture of trowels without any feedback about the robot velocity.     

Force control of robots with nonlinearities

This paper explores two practical issues related to the force control of manipulators. The first issue examined is how system stability is effected by commonly occurring manipulator nonlinearities, such as sampled-data, control signal saturation and slip-stick friction. It is shown that discretely implemented force control algorithms can drive the feedback force controlled manipulator into a limit cycle, even for a very small sampling period that by far satisfies Shannon's sampling theorem. The bounds of stability are enhanced by the presence of control signal saturation and slip stick friction. The second issue investigated is the inclusion of a high gain inner position loop as a means to minimize the unpredictability in the steady state error due to slip-stick friction. In order to support the theoretical conclusions, experiments were performed with the PUMP 560 industrial robot testbed facility developed at Colorado State University.