Cost-efficient drilling using industrial robots with high-bandwidth force feedback

Here we present a method for high-precision drilling using an industrial robot with high-bandwidth force feedback, which is used for building up pressure to clamp-up an end-effector to the work-piece surface prior to drilling. The focus is to eliminate the sliding movement (skating) of the end-effector during the clamp-up of the end-effector to the work-piece surface, an undesired effect that is due to the comparatively low mechanical stiffness of typical serial industrial robots. This compliance also makes the robot deflect due to the cutting forces, resulting in poor hole position accuracy and to some extent in poor hole quality. Recently, functionality for high-bandwidth force control has found its way into industrial robot control systems. This could potentially open up the possibility for robotic drilling systems with improved performance, using only standard systems without excessive extra hardware and calibration techniques. Instead of automation with expensive fixtures and precise machinery, our approach was to make use of standard low-cost robot equipment in combination with sensor feedback. The resulting sliding suppression control results in greatly improved hole positioning and quality. The conceptual idea behind the force control is useful also in many other robotic applications requiring external sensor feedback control.     

Neural Network Force Control for Industrial Robots

In this paper, we present a hierarchical force control framework consisting of a high level control system based on neural network and the existing motion control system of a manipulator in the low level. Inputs of the neural network are the contact force error and estimated stiffness of the contacted environment. The output of the neural network is the position command for the position controller of industrial robots. A MITSUBISHI MELFA RV-M1 industrial robot equipped with a BL Force/Torque sensor is utilized for implementing the hierarchical neural network force control system. Successful experiments for various contact motions are carried out. Additionally, the proposed neural network force controller together with the master/slave control method are used in dual-industrial robot systems. Successful experiments are carried out for the dual-robot system handling an object.     

Cooperative Control of a 3D Dual-Flexible-Arm Robot

This paper discusses cooperative control of a dual-flexible-arm robot to handle a rigid object in three-dimensional space. The proposed control scheme integrates hybrid position/force control and vibration suppression control. To derive the control scheme, kinematics and dynamics of the robot when it forms a closed kinematic chain is discussed. Kinematics is described using workspace force, velocity and position vectors, and hybrid position/force control is extended from that on dual-rigid-arm robots. Dynamics is derived from constraint conditions and the lumped-mass-spring model of the flexible robots and an object. The vibration suppression control is calculated from the deflections of the flexible links and the dynamics. Experiments on cooperative control are performed. The absolute positions/orientations and internal forces/moments are controlled using the robot, each arm of which has two flexible links, seven joints and a force/torque sensor. The results illustrate that the robot handled the rigid object damping links' vibration successfully in three-dimensional space.     

Robotic sanding system for new designed furniture with free-formed surface

In this paper, a sanding system based on an industrial robot with a surface following controller is proposed for the sanding process of wooden materials constructing furniture. Handy air-driven tools can be easily attached to the tip of the robot arm via a compact force sensor. The robotic sanding system is called the 3D robot sander. The robot sander has two novel features. One is that the polishing force acting between the tool and wooden workpiece is delicately controlled to track a desired value, e.g., 2 kgf. The polishing force is defined as the resultant force of the contact force and kinetic friction force. The other is that no complicated teaching operation is required to obtain a desired trajectory of the tool. Cutter location (CL) data, which are tool paths generated by a CAD/CAM system, are directly used for the basic trajectory of the handy tool attached to the robot arm. The robot sander can be applied to the sanding task of free-formed curved surface with which conventional sanding machines have not been able to cope. The effectiveness and promise are shown and discussed through a few experiments.     

Experiments in contact control

This article describes the implementation, experimentation, and application of contact control schemes for a 7-DOF Robotics Research arm. The contact forces and torques are measured in the sensor frame by the 6-axis force/torque sensor mounted at the wrist, are compensated for gravity, and then are transformed to the tool frame in which the contact task is defined and executed. The contact control schemes are implemented on the existing robot Cartesian position control system at 400Hz, do not require force rate information, and are extremely simple and computationally fast. Three types of contact control schemes are presented: compliance control, force control, and dual-mode control. In the compliance control scheme, the contact force is fed back through a lag-plus-feedforward compliance controller so that the end-effector behaves like a spring with adjustable stiffness; thus the contact force can be controlled by the reference position command. In the force control scheme, a force setpoint is used as the command input and a proportional-plus-integral force controller is employed to ensure that the contact force tracks the force setpoint accurately. In the dual-mode control scheme, the end-effector approaches and impacts the reaction surface in compliance mode, and the control scheme is then switched automatically to force mode after the initial contact has been established. Experimental results are presented to demonstrate contact with hard and soft surfaces under the three proposed control schemes. The article is concluded with the application of the proposed schemes to perform a contact-based eddy-current inspection task. In this task, the robot first approaches the inspection surface in compliance control until it feels that it has touched the surface, and then automatically levels the end-effector on the surface. The robot control system then transitions to force control and applies the desired force on the surface while executing a scanning motion. At the completion of the inspection task, the robot first relaxes the applied force and then retracts from the surface. © 1996 John Wiley & Sons, Inc.     

基于变刚度自适应导纳机制的机械臂恒力控制

工业机械臂在诸如打磨抛光等接触式作业任务中对环境刚度信息存在一定的依赖性, 未知环境刚度信息将严重影响机器人的力位控制精度, 使得作业效果难以得到保证. 为解决环境信息不足或未知情况下的力/位置精确控制问题, 本文首先提出了一种新的自适应环境刚度在线估计方法, 针对时变的环境刚度进行实时估计, 由此预测生成后继的机械臂参考轨迹点, 随后提出了一种根据力跟踪误差实时调整末端工具手刚度系数的变刚度导纳恒力控制方法, 并结合李雅普诺夫稳定性理论给出了整体控制律的收敛性证明. 针对刚柔两种末端工具手和多种不同的曲面工件开展了实验研究, 并与传统PID控制方法和传统导纳控制方法进行了对比, 其结果表明本文所提出的复合控制方法可在不同工况条件下实现机器人运动过程中接触力的快速柔顺调节, 并获得4.55%以内的最优力控误差效果, 证明了本文所提出方法的有效性与可行性.     

Force-guided motions of a 6-d.o.f. industrial robot with a joint space approach

This article deals with the interaction between humans and industrial robots, more specifically with the new design and implementation of an algorithm for force-guided motions of a 6-d.o.f. robot. It may be used to comfortably teach positions without using any teaching pendant or for some assistance tasks. For this purpose, from readings of the force/torque sensor mounted in the robot wrist, the gravity forces and torques first have to be eliminated. To control the robot in joint space, it is then convenient to transform the external force and torque values from Cartesian space into joint space using the manipulator transposed Jacobian. This is why with the present approach the Jacobian matrix of the robot used was calculated. Now, from the computed joint torques, suitable position commands of the robot arm can be generated to obtain the desired behavior. A suggestion for this desired behavior is also included in this article. It is based on the impedance control approach in joint space. The proposed algorithm was implemented with the standard Stäubli RX90B industrial robot.     

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.     

基于阻抗模型的下肢康复机器人交互控制系统设计

为帮助下肢功能障碍患者进行康复训练,设计了下肢康复机器人。对于该机器人的控制,采用传统系统无法柔顺控制,导致机器人运动轨迹偏离预设轨迹。针对该现象,提出了基于阻抗模型的下肢康复机器人交互控制系统设计。通过分析总体控制方案,设计系统硬件结构框图。采用L型二维力传感器,确定两个方向的人机交互力。使用绝对值编码器安装在各个关节处,其输出值作为髋关节、膝关节、踝关节电机的转动位置,增量编码器安装在电机轴上,测量值用来作为后期控制方法的输入参数。构建阻抗控制模型,能够调节机器人位置和速度,具有消除力误差功能。依据此力矩对参考运动轨迹进行设计,实时获取患者康复训练的跟踪、主动柔顺和接近状态信息。在柔顺训练实验测出人机交互力,通过实验结果知,在检测到人体主动力矩异常时,系统能够重新优化轨迹,具有良好柔顺控制效果。     

Integrated approach to robotic machining with macro/micro-actuation

A novel integrated approach to high-accuracy machining with industrial robots is presented in this paper. By combining a conventional industrial robot with an external compensation mechanism, a significantly higher bandwidth of the control of the relative position between the tool and the workpiece can be achieved. A model-based feedback controller for the compensation mechanism, as well as a mid-ranging control architecture for the combined system with the robot and the compensation mechanism are developed. The system performance is evaluated in extensive machining experiments, and the workpiece accuracies achieved are quantified and compared to the corresponding results obtained with state-of-the-art approaches to robotic machining. It is shown that the proposed approach to machining offers significantly higher accuracy, up to eight times improvement for milling in steel, where the required process forces, and thus the exhibited position deviations of the robot, are significant.     

Position-Based Fuzzy Force Control for Dual Industrial Robots

In this paper, a fuzzy force control framework is proposed for dual-industrial robot systems. The master/slave control method is used in dual-robot systems. Two MITSUBISHI MELFA RV-M1 industrial robots, one is equipped with an BL Force/Torque sensor and the other is not, are utilized for implementing the dual-arm system. In order to adapt various stiffness of the holding object, an adaptable fuzzy force control scheme has been proposed to improve the performance. The ability of the adaptable force control system is achieved by tuning the scaling factor of the fuzzy logic controller. Successful experiments are carried out for the dual-robot system handling an object.     

附加力外环的机器人力／位置自适应模糊控制

提出一种由神经网络训练模糊控制规则的自适应模糊控制器,并应用附加力外环的机器人力／位置控制。在不改变一般工业机器人原有位置控制的前提下,实现力／位置自适应模糊控制。实验结果表明,该方法可使机器人控制系统对工作环境接触刚度的自适应能力得到显著改善。     

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.     

Robotic execution of everyday tasks by means of external vision/force control

In this article, we present an integrated manipulation framework for a service robot, that allows to interact with articulated objects at home environments through the coupling of vision and force modalities. We consider a robot which is observing simultaneously his hand and the object to manipulate, by using an external camera (i.e. robot head). Task-oriented grasping algorithms (Proc of IEEE Int Conf on robotics and automation, pp 1794–1799, 2007) are used in order to plan a suitable grasp on the object according to the task to perform. A new vision/force coupling approach (Int Conf on advanced robotics, 2007), based on external control, is used in order to, first, guide the robot hand towards the grasp position and, second, perform the task taking into account external forces. The coupling between these two complementary sensor modalities provides the robot with robustness against uncertainties in models and positioning. A position-based visual servoing control law has been designed in order to continuously align the robot hand with respect to the object that is being manipulated, independently of camera position. This allows to freely move the camera while the task is being executed and makes this approach amenable to be integrated in current humanoid robots without the need of hand-eye calibration. Experimental results on a real robot interacting with different kind of doors are presented.     

Updating workpiece geometry using robotic sensor information gathered during contact tasks

During robotic contact tasks, geometric information of the workpiece is used to specify the position of the robot’s hand on the workpiece and the direction of force control. This geometry is idealized in a typical CAD file, but due to manufacturing precision or wear, the actual workpiece geometry is inevitably deviated from the desired geometry. Furthermore, when the workpiece is mounted, position and orientation inaccuracies emerge. In this paper, we investigate two questions: (1) Can the workpiece geometry in the CAD file be used to control a robot in contact with an inaccurately placed workpiece?; and (2) Once the task is performed, how can the robot’s sensor information be used to update the geometry of the workpiece? A methodology is developed to solve robotic control problems with workpiece position and geometry inaccuracies. Once performed, the CAD file image is displaced to fit the sensed trajectory of the robot’s hand. Finally, the workpiece image geometry is modified using a least squares approximation to fit the sensed data more accurately. In the end, the robot performs the contact task while gathering information that is used to update the original CAD file geometry. The methodologies are demonstrated through a simulation experiment that requires a robot to shave a geometrically altered face that is inaccurately positioned.     

基于D-H法的农业采摘机器人运动协作控制系统设计

为提升农业采摘机器人运动协作控制性能,降低机器人碰撞概率,利用D-H法优化设计机器人运动协作控制系统。改装位置、力矩以及碰撞传感器设备,优化运动协作控制器与驱动器,调整系统通信模块结构,完成硬件系统的优化。利用D-H法构建农业采摘机器人数学模型,在该模型下,利用传感器设备实现机器人实时位姿的量化描述,通过机器人采摘流程的模拟,分配机器人运动协作任务,从位置和姿态等多个方面,确定运动协作控制目标,经过受力分析求解机器人实际作用力,最终通过控制量的计算,实现农业采摘机器人的运动协作控制功能。通过系统测试实验得出结论：与传统控制系统相比,机器人位置、姿态角和作用力的控制误差分别降低了约40mm、0.2°和1.2N,在优化设计系统控制下,机器人的碰撞次数得到明显降低。     

Remote control of space robots

A method for the remote control of a space robot is proposed for the case of large delays in the transmission of control signals from the Earth to the local robot control system and in feedback signals. The method involves the use of the model of the space robot and its current environment with the simulation of gravity conditions at the ground control center. In this model environment, the operator should carry out the required actions by controlling the space robot model in the master-slave mode using an arm with six degrees of freedom capable of reflecting the interaction force of a model robot working tool with models of the objects of the environment. The arm movement trajectory and the law of time variation of the reflected interaction force vector are program-based for the local space robot control system and should be executed by it upon reception from the ground control center. The robot’s possible erroneous actions generated by the inevitable inaccuracy of the environment model are compensated by the proposed method of programmed trajectory correction. In accordance with it, in order to generate correction signals, additional information received from different sensors is used. These sensors can be installed on both the model and space robot itself. This information includes data on the mutual position of a robot’s working tool and models of the objects of the environment, as well as on the interaction forces between them. The paper presents a detailed theoretical justification of the proposed approach and experimental results that confirm the theoretical conclusions.     

A unified multimodal control framework for human–robot interaction

In human–robot interaction, the robot controller must reactively adapt to sudden changes in the environment (due to unpredictable human behaviour). This often requires operating different modes, and managing sudden signal changes from heterogeneous sensor data. In this paper, we present a multimodal sensor-based controller, enabling a robot to adapt to changes in the sensor signals (here, changes in the human collaborator behaviour). Our controller is based on a unified task formalism, and in contrast with classical hybrid visicn–force–position control, it enables smooth transitions and weighted combinations of the sensor tasks. The approach is validated in a mock-up industrial scenario, where pose, vision (from both traditional camera and Kinect), and force tasks must be realized either exclusively or simultaneously, for human–robot collaboration.     

Continuous shape-grinding experiment based on model-independent force/position hybrid control method with on-line spline approximation

Based on the analysis of interaction between manipulator’s hand and working object, a model representing the constrained dynamics of robot is first discussed. The constraint forces are expressed by algebraic function of states, input generalized forces, and constraint condition, and then a decoupling control method of force and position of manipulator’s hand tip is proposed. In order to give the grinding system the ability to adapt to any object shape being changed by the grinding, estimating function of the constraint condition in real time for the adaptive force/position control was added, which is indispensable for the proposed method without using force sensor. This paper explores whether the performance of the proposed controller is independent of alloy work-piece models or not. The experimental result is shown to verify the feature of the decoupling control of force and position of the tip.     

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