Transparent and Stretchable Interactive Human Machine Interface Based on Patterned Graphene Heterostructures

An interactive human‐machine interface (iHMI) enables humans to control hardware and collect feedback information. In particular, wearable iHMI systems have attracted tremendous attention owing to their potential for use in personal mobile electronics and the Internet of Things. Although significant progress has been made in the development of iHMI systems, those based on rigid electronics have constraints in terms of wearability, comfortability, signal‐to‐noise ratio (SNR), and aesthetics. Herein the fabrication of a transparent and stretchable iHMI system composed of wearable mechanical sensors and stimulators is reported. The ultrathin and lightweight design of the system allows superior wearability and high SNR. The use of conductive/piezoelectric graphene heterostructures, which consist of poly(l ‐lactic acid), single‐walled carbon nanotubes, and silver nanowires, results in high transparency, excellent performance, and low power consumption as well as mechanical deformability. The control of a robot arm for various motions and the feedback stimulation upon successful executions of commands are demonstrated using the wearable iHMI system.     

System Design and Control of Anthropomorphic Walking Robot LOLA

This paper presents the 25-DOF full-size humanoid robot LOLA . Our goal is to realize fast and human-like walking. Furthermore, we want to increase the robot’s autonomous, vision-guided walking capabilities. LOLA is characterized by a redundant kinematic configuration, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution to achieve good dynamic performance. Center of mass trajectories are calculated in real-time from footstep locations using a spline collocation method. Reference trajectories are modified by a stabilizing control system based on hybrid force/position control with an inner joint position control loop.      

Programming by touch: the different way of human-robot interaction

Mobile service robots will share their workspaces, e.g., offices, hospitals, or households, with humans. Thus, a direct contact between man and machine is inevitable. Robots equipped with appropriate sensors can sense the touch. In this paper, we present how an unskilled user can intuitively teach the lightweight robot at the German Aerospace Center (DLR), We/spl szlig/ling, Germany, just by touching the arm. Programming by "touch" is very intuitive as you take the robot by the hand and demonstrate the movements. This feature can also be used to interact with the service robot while executing a task. Therefore, if our seven-degrees-of-freedom robot arm senses a touch, it will react by an evasive motion of the touched links while keeping the orientation of the tool center point.     

Vibration Absorption Control of Industrial Robots by Acceleration Feedback

This paper describes an electrical control method of absorbing arm vibrations of industrial robots. Arm vibration problems are divided into two categories: resonance vibration phenomenon depending on actuator velocity and transient oscillations caused by acceleration change of actuators. Because resonance frequency of an industrial robot changes more than double due to the arm posture, mechanical vibration absorbing methods may not be easily utilized. The method applied in this paper is to compose dampers as electric manners by utilizing arm acceleration feedback to actuators of an industrial robot. Acceleration sensors are attached on three axes which construct a robot arm. Acceleration signals are fed back to the corresponding actuators passed through phase compensation circuits. By experiments applied to an industrial robot, this method has been proved to be effective in eliminating both resonance and transient vibrations. According to this control, a smart motion industrial robot which does not have resonance characteristics and operates speedily and smoothly has been realized.     

Articulated hybrid mobile robot mechanism with compounded mobility and manipulation and on-board wireless sensor/actuator control interfaces

This paper presents the development of a remotely operated mobile robot system with a hybrid mechanism whereby the locomotion platform and manipulator arm are designed as one entity to support both locomotion and manipulation interchangeably. The mechanical design is briefly described as well as the dynamic simulations used to analyze the robot mobility and functionality. As part of the development, this paper mainly focuses on a new generalized control hardware architecture based on embedded on-board wireless communication network between the robot’s subsystems. This approach results in a modular control hardware architecture since no wire connections are used between the actuators and sensors in each of the mobile robot subsystems and also provides operational fault-tolerance. The effectiveness of this approach is experimentally demonstrated and validated by implementing it in the hybrid mobile robot system. The new control hardware architecture and mechanical design demonstrate the qualitative and quantitative performance improvements of the mobile robot in terms of the new locomotion and manipulation capabilities it provides. Experimental results are presented to demonstrate new operative tasks that the robot was able to accomplish, such as traversing challenging obstacles, and manipulating objects of various capacities; functions often required in various challenging applications, such as search and rescue missions, hazardous site inspections, and planetary explorations.     

基于3DS Max 与OpenGL的机械臂仿真与控制

阐述了在以Vc＋＋6．0为平台的基础上，利用3DSMax与OpenGL对机械臂进行可视化三维仿真的一种方法。为满足蒸汽发生器六轴机械臂检修控制系统的要求，建立一个多功能的实验仿真平台。一方面从正解、反解两个方面对机械臂进行了运动学分析，从而实现了机械臂的各轴在多种控制下的运动；另一方面将OpenGL与3DSMax相结合建立系统模型，给出机械臂在空间运动与抓顶的三维动画实现过程。实验结果证明仿真平台在实际工程中具有一定价值。     

Frequency reshaped quadratic control of a low-cost human-level performance belt-driven robot

Belt-driven robots are desirable for many industrial applications that require a fast response for a relatively large amount of travel in a system. A belt-drive is a simple, lightweight device that is also cost effective in comparison to other methods of arm positioning. The tradeoff of a belt-driven robot is the need for an effective control strategy to reject time-varying disturbances due to the belt stiffness variation and the presence of resonance excited by disturbances of high frequencies. In this paper, we present the dynamic model and control of a low-cost belt-driven robot.We present here the modeling and control of an intelligent integrated belt-driven manipulator (IIBM) developed at Georgia Tech. The belt-driven robot is a low-cost human-level performance robot, specifically meant to meet or exceed the performance of a human taking shrink wrapped packages off a conveyor and placing them in a basket for delivery. Therefore, such attributes as speed and accuracy are dictated by the level of performance a human can achieve. The control design for the IIBM presents a challenge in that a control system for the belt-driven axis must be designed by using a low-order plant model that is robust enough to variations in both the parameter changes and the un-modeled high frequency dynamics. For these reasons, we investigate the use of frequency reshaped linear quadratic (FRLQ)) control in the development of a low-cost IIBM, which combines the time domain linear quadratic optimal control design with classical frequency response methods.The control strategy, based on the FRLQ method, has been implemented on the first axis of an IIBM. The performance has been evaluated analytically by simulation and experimentally, the results of which are compared against the control system originally used by the IIBM designers, a well-tuned PD controller. Experimental implementation has demonstrated that the frequency reshaped linear quadratic control has a potential to significantly improve the performance of the belt-driven robot.     

Robust speed control system considering vibration suppressioncaused by angular transmission error of planetary gear

This paper proposes a new robust speed control to suppress vibration caused by angular transmission error of planetary gears. For this purpose, this paper first constructs a new numerical simulation model of angular transmission error of planetary gear, which is confirmed by experimental data from a robot arm. Next, in order to suppress the vibration caused by angular transmission error, we propose a robust speed control system based on disturbance observer and coprime factorization. Numerical simulation results show that the proposed system regulates the angular speed of motor satisfactorily, and it suppresses the vibration caused by angular transmission error     

Control of articulated robot arm with sensory feedback: laser beamtracking system

A method for the trajectory tracking control of an articulated robot arm using sensory feedback is presented. First, a general control algorithm for such a problem is presented. To implement sensory feedback effectively, the dynamics of a robot arm is described in the task coordinate system. Then the dynamics of the robot arm in the task coordinate system are linearized using nonlinear feedback. Because the linearization cannot be done completely because of variations and identification errors of the physical parameters of a robot arm, a robust controller is designed so that the effect of parameter variations and errors can be lessened. The control law is shown to be simplified by the use of high-gain feedback. The simplification can make the implementation of the control law very easy. The proposed algorithm is applied to the trajectory-tracking control of an articulated robot arm using a laser beam. The experiments show that the proposed algorithm works well for such a sensory feedback system     

Intelligent optimal control of single-link flexible robot arm

This paper addresses the design and properties of an intelligent optimal control for a nonlinear flexible robot arm that is driven by a permanent-magnet synchronous servo motor. First, the dynamic model of a flexible robot arm system with a tip mass is introduced. When the tip mass of the flexible robot arm is a rigid body, not only bending vibration but also torsional vibration are occurred. In this paper, the vibration states of the nonlinear system are assumed to he unmeasurable, i.e., only the actuator position can be acquired to feed into a suitable control system for stabilizing the vibration states indirectly. Then, an intelligent optimal control system is proposed to control the motor-mechanism coupling system for periodic motion. In the intelligent optimal control system a fuzzy neural network controller is used to learn a nonlinear function in the optimal control law, and a robust controller is designed to compensate the approximation error. Moreover, a simple adaptive algorithm is proposed to adjust the uncertain bound in the robust controller avoiding the chattering phenomena. The control laws of the intelligent optimal control system are derived in the sense of optimal control technique and Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. In addition, numerical simulation and experimental results are given to verify the effectiveness of the proposed control scheme.     

Adaptive neural network based controller for robots

A new Adaptive Neural Network (ANN) controller for robot trajectory trackingproblem is developed. A novel and efficient training algorithm for the proposed controller ispresented in this paper. The proposed training algorithm is based on updating the weights of thenetwork each step by minimizing the quadrant tracking errors and their derivatives.A simulation study is carried out on a polar robot manipulator to assure the effectivenessof the proposed trajectory tracking robot control system. The effects of the new controllerparameters and noisy external load disturbances on the control performance are studied. Thesimulation results of the proposed adaptive ANN controller are compared with those of aconventional ANN controller. The obtained results assured the robustness of the proposed ANNcontroller for: (i) uncertainties of the robot arm dynamic model and/or parameters, (ii) variousnoisy external load disturbances. Also, the simulation results assure the effectiveness of theproposed adaptive ANN controller against the conventional ANN one.     

双臂六自由度空间机器人广义雅可比矩阵的推导

本文建立了双臂六自由度空间机器人的运动学模型,基于此模型,推导出描述机械手末端运动速度与各关节运动速度关系的广义雅可比矩阵(GJM).较现有的其他推导GJM方法相比,导出的GJM求解公式显式、易求,可直接对GJM表达式中各参数赋值,求出GJM.本文的建模方法适合采用分解运动速度(RMRC)控制方法.计算机仿真中,给出了基于RMRC控制方法,利用本文导出的GJM求解公式实现了对机械臂的运动控制.     

Fault-tolerant control system of flexible arm for sensor fault by using reaction force observer

In recent years, control system reliability has received much attention with increase of situations where computer-controlled systems such as robot control systems are used. In order to improve reliability, control systems need to have abilities to detect a fault (fault detection) and to maintain the stability and the control performance (fault tolerance). In this paper, we address the vibration suppression control of a one-link flexible arm robot. Vibration suppression is realized by an additional feedback of a strain gauge sensor attached to the arm besides motor position. However, a sensor fault (e.g., disconnection) may degrade the control performance and make the control system unstable at its worst. In this paper, we propose a fault-tolerant control system for strain gauge sensor fault. The proposed control system estimates a strain gauge sensor signal based on the reaction force observer and detects the fault by monitoring the estimation error. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault-mode controller so as to maintain the stability and the control performance. We apply the proposed control system to the vibration suppression control system of a one-link flexible arm robot and confirm the effectiveness of the proposed control system by some experiments.     

From biological inspiration toward next-generation manipulators: manipulator control focused on human tasks

This paper presents our approach to extend the niche of behavior-based robotics toward manipulation. We use results from neuroscience to derive some qualitative design rules for the mechanics of the manipulator, resulting in a next-generation manipulator, the "soft arm". By defining the basic behaviors of the manipulator as trajectory-producing behaviors (which is also biologically plausible), we have designed a first test case: writing on a board with a mobile manipulator. The soft arm has not yet been developed; therefore, we have emulated such a soft robot arm on an industrial robot.     

忆阻PID控制器在机械臂实时控制系统中的应用研究

目前忆阻器在忆阻神经形态电路方面的研究日渐成熟,但将其应用于实时控制电路还有待完善.本文以二关节机械臂作为研究对象,将电压阀控忆阻器与传统PID控制器相结合,设计了可用于实时电路系统的忆阻PID（M-PID）控制系统.并创新性的利用MOS管自身开关阀值,设计了带有"零态"区间的阀值忆阻器控制电路,这可有效避免因控制器频繁切换带给系统的震荡.论文利用Matlab仿真软件,从阶跃响应及位置跟踪两个层面对所设计的控制系统进行了仿真分析.仿真结果表明：所提M-PID控制算法可有效改善二关节机械臂控制系统的稳态和动态品质.     

Redundancy resolution of the human arm and an upper limb exoskeleton

The human arm has 7 degrees of freedom (DOF) while only 6 DOF are required to position the wrist and orient the palm. Thus, the inverse kinematics of an human arm has a nonunique solution. Resolving this redundancy becomes critical as the human interacts with a wearable robot and the inverse kinematics solution of these two coupled systems must be identical to guarantee an seamless integration. The redundancy of the arm can be formulated by defining the swivel angle, the rotation angle of the plane defined by the upper and lower arm around a virtual axis that connects the shoulder and wrist joints. Analyzing reaching tasks recorded with a motion capture system indicates that the swivel angle is selected such that when the elbow joint is flexed, the palm points to the head. Based on these experimental results, a new criterion is formed to resolve the human arm redundancy. This criterion was implemented into the control algorithm of an upper limb 7-DOF wearable robot. Experimental results indicate that by using the proposed redundancy resolution criterion, the error between the predicted and the actual swivel angle adopted by the motor control system is less then 5°.     

Development of the intake system for the SnowEater robot

The development of the intake system for the SnowEater robot is presented in this paper. The SnowEater robot is a small, lightweight and low powered autonomous machine, designed to remove and compact snow from small areas (less than 30 m²). Its design includes four interacting systems to accomplish the task. These systems are the intake, crawler, compressing and navigation system. This paper focuses on the intake system and its cooperative control with the crawler system. The intake system has three screws to collect the snow. The used control encloses the screw alternating motion and the tracked robot motion; the stable autonomous operation under different snow conditions is designed considering the snow income and its processing speed. Furthermore, an altitude mechanism is presented to enhance the mobility in deep snow conditions.     

Improving the Positioning Accuracy of a Neurosurgical Robot System

This paper discusses the overall positioning accuracy of a neurosurgical robot system. First, the overall positioning accuracy of the robot system is analyzed and formulated. Then, the efforts are focused on improving the positioning accuracy of the robot arm. A revised Denavit--Hartenberg (D-K) kinematic model is addressed to describe two nearly parallel joint axes for the calibration of the robot. The joint transmitting error of the robot is compensated by using a backpropagation (BP) neural network. Finally, the absolute positioning accuracy of the robot arm is measured. A phantom is designed to simulate the clinical workflow of the robot-assisted neurosurgery for measuring the overall positioning accuracy of the robot system. The results show that the positioning error of the robot arm is less than 1 mm, which is comparable to that of stereotactic frames; and that the overall positioning error of the robot system is caused mainly by target registration error, which proves the effectiveness of our efforts.     

Kalman-Filter-Based Sensor Integration of Variable Power Assist Control Based on Human Stiffness Estimation

In applications such as robot collaborating with human operators, the robot system must operate more slowly and be more compliant to safe user interaction. Moreover, a consideration of the dynamic properties of human operators is also important for the human application. According to such requirements, this paper presents a novel sensorless force control approach for the robot-assisted motion of the human arm. A twin direct-drive motor system with a wire rope has been developed to provide a precise force sensation and safety for human-robot interaction. In order to control the wire rope tension and human interaction force, two mode designs of the force control are realized. The common mode is utilized for the control of wire rope tension. In the differential mode, the Kalman-filter-based sensor integration for the interaction force observer is proposed in this paper. By combining two motor encoders and a commercial acceleration sensor together, white Gaussian noise is reduced, and high accurate feedback of the contact force is obtained. A variable power assist control method based on a real-time estimation of the stiffness of the human arm is also introduced. By considering the stiffness in human arm movements, this method increases the efficiency of the force control system and realizes comfortable force for human-robot interaction. The effectiveness of the method is verified by experimental results.