A Serial-Type Dual Actuator Unit With Planetary Gear Train: Basic Design and Applications

Control of a robot manipulator in contact with the environment is usually conducted by a direct feedback control system using a force–torque sensor or an indirect impedance control scheme. Although these methods have been successfully applied to many applications, simultaneous control of force and position cannot be achieved. To cope with such problems, this paper proposes a novel design of a dual actuator unit (DAU) composed of two actuators and a planetary gear train to provide the capability of simultaneous control of position and stiffness. Since one actuator controls position and the other actuator modulates stiffness, the DAU can control the position and stiffness simultaneously at the same joint. Both the torque exerted on the joint and the stiffness of the environment can be estimated without an expensive force sensor. Various experiments demonstrate that the DAU can provide good performance for position tracking, force estimation, and environment estimation.      

Torque-balancing algorithm for the redundantly actuated parallel mechanism

In this work, a joint torque distribution algorithm of parallel mechanism (PM) with one redundant actuator is suggested. The algorithm is effective in avoiding the joint torque saturations. In the algorithm, the force equations are modified into the line equations representing the joint torque solutions. Then, the optimal joint torque distribution is found only by searching the intersections among the line equations. A comparative study of the suggested algorithm with the other typical actuator redundancy resolution algorithms, such as the minimum-norm (MN) torque algorithm, the weighted MN torque algorithm, and a task-priority algorithm, is conducted through simulations and experiments with a 3-DOF planar PM with one actuator redundancy. The simulations and experiments confirm that the suggested redundant actuation algorithm shows an enhanced performance in terms of joint torque limit avoidance and minimum output force/torque distortion over other preexisting algorithms.     

Quasi-Linear Position Relationships in Rolling Joints

The relationship between the angle of joint position and a linear actuation position, together with appropriate torque relationships, is developed for rolling contact joints with offset insertion by first considering more simple situations. The position relationship can be made quasi-linear by a suitable choice of dimensions, a factor which may be of consequence in design studies of orthotic and prosthetic upper extremity devices and in the field of manipulators.     

Development of a Biofeedback Therapeutic-Exercise-Supporting Manipulator

Although much equipment for physical therapy has been developed, equipment to improve the quality of physical therapy is scarce. We propose a robotic biofeedback exercise device that can display human joint torque and muscle force during training without a problematic electromyogram (EMG). The purpose is to increase the therapeutic value by understanding a person's condition during exercise and to provide an incentive to improve performance. The manipulator supports lower limb rehabilitation in the sagittal plane. With its ability to adjust the maximum speed and the time constant, the manipulator provides simultaneous and safe isokinetic exercise for the knee and hip joints. This paper describes the estimation of the human joint torque and muscle force. The display of the joint torque and the muscle force is realized during exercise of the knee joint using the developed manipulator. The estimation of the muscle force from Crowninshield's method and Hase's method generally agrees with the EMG.     

Design and control of tele-matched surgery robot

In the present paper, we develop a tele-matched surgery robot for a precise force reflection, and stable and intuitive operation. The term ‘tele-matched’ means that the motions of master and slave robots are matched precisely by bilateral teleoperation. The developed tele-matched surgery robot has three main features: (1) Coupling forces among joints of slave end-effector are removed. (2) Power transmission mechanism of slave robot is designed suitable enough for torque estimation without a torque sensor. (3) The motion of each joint of master robot precisely matches to that of slave robot. Consequently, as the key contributions of this paper, a new tendon mechanism is designed to remove the coupling forces, a torque estimation scheme is used to estimate the external forces without using any physical sensors, and by the motion matching between the master and slave robots, a surgeon can operate the slave motion by intuitively controlling the master device. The effectiveness of the developed robot is verified through a number of experiments.     

Harnessing the Actuation Potential of Solid‐State Intercalation Compounds

High‐strain, high‐force mechanical actuation technologies are desirable for numerous applications ranging from microelectromechanical systems (MEMS) to large‐scale “smart structures” that are able to change shape to optimize performance. Here we show that electrochemical intercalation of inorganic compounds of high elastic modulus offers a low‐voltage mechanism (less than 5 V) with intrinsic energy density approaching that of hydraulics and more than a hundred times greater than that of existing field‐operated mechanisms, such as piezostriction and magnetostriction. Exploitation of the reversible crystallographic strains (several percent) of intercalation compounds while under high stress is key to realization of the available energy. Using a micromachined actuator design, we test the strain capability of oriented graphite due to electrochemical lithiation under stresses up to 200 MPa. We further demonstrate that simultaneous electrochemical expansion of the LiCoO₂/graphite cathode/anode couple can be exploited for actuation under stresses up to ～ 20 MPa in laminated macroscopic composite actuators of similar design to current lithium‐ion batteries. While the transport‐limited actuation mechanism of these devices results in intrinsically slower actuation compared to most ferroic materials, we demonstrate up to 6.7 mHz (150 s) cyclic actuation in a laminated actuator designed for a high charge/discharge rate. The potential for a new class of high‐strain, high‐force, moderate‐frequency actuators suitable for a broad range of applications is suggested.     

Control of switched reluctance motor torque for force controlapplications

The paper presents a method for controlling switched reluctance motor (SRM) torque for force control applications. SRMs are used in AdeptOne robots, and the authors perform experiments with two robots, controlled in coordination, in grasping and manipulation of various objects. The object and robot parameters are not exactly known, and adaptive methods are used to control the overall system. These methods are model-based control techniques which require high bandwidth torque control. This requirement is typical for high precision mechanisms. SRM characteristics are very nonlinear. In particular the torque ripple, friction, and the torque versus position and current relationships were analyzed in the context mentioned above, and specifically, for force control applications. The proposed method is based on a new commutation algorithm and a measured torque versus position and current relationship, used to smooth the SRM's torque ripple, hence generating a torque output nearly independent of position. Furthermore, the internal friction is estimated on-line, and compensated for. This renders a high accuracy torque tracking. The torque control method is based on feedback from the motor angular velocity, motor angle, armature current, and feedforward for friction compensation and cancellation of nonlinear effects. The method has been tested experimentally on Adept motors and the results were very encouraging. The method has been also used for adaptive control of two coordinated Adept robots     

Modular integrated longitudinal and lateral vehicle stability control for electric vehicles

In this paper, the problem of integrated longitudinal and lateral vehicle stability control is addressed using a modular optimal control structure. The optimization process of the high level model predictive control (MPC) controller determines required longitudinal force and yaw moment adjustments to minimize the error between vehicle longitudinal and lateral vehicle stability dynamic states with respect to the target courses. The low level controller is designed to optimally regulate torque at each wheel based on the control inputs of the high level controller, and distribute required torque between the wheels via actuation system. The actuation system that is utilized to implement the proposed control structure functions based on all-wheel drive technology that can provide active control of both traction and yaw moment control with differential torque. The multi-layered structure of the control system allows modularity in design. The performance of the control structure is investigated by conducting experimental tests. The experimental tests have been performed on an electric Chevrolet Equinox vehicle equipped with four independent motors. The results show that the integration of the vehicle longitudinal and lateral dynamics preserves vehicle stability in a planar motion and improves the vehicle dynamic response, especially in challenging driving maneuvers.     

Experimental comparison of antagonistic hydraulic muscle actuation under single/dual and zero/overlapped servovalve configurations

There are many studies on the antagonistic actuation of pneumatic artificial muscles; however, hydraulic artificial muscles have been rarely studied. The purpose of this study is to compare the characteristics of the antagonistic actuation of hydraulic muscles under different servovalve configurations. A dual-servovalve configuration can independently control the muscles on both sides, whereas a single-servovalve configuration cannot although it has a cost advantage. A zerolapped-servovalve has better response performance, whereas an overlapped-servovalve can use a higher gain in the controller. We use a single-zerolapped-servovalve as a reference, and compare it with a dual-zerolapped-servovalve, a single-overlapped-servovalve, and a dual-overlapped-servovalve configuration under position control and torque control for antagonistic actuation. Experimental results show that only the dual-servovalve configuration can adjust the range of the average pressure under position control or directly control the average pressure under torque control, thereby adjusting the compliance of the joint. Zerolapped servovalve shows better tracking performance; however, the overlapped servovalve shows better stability under higher proportional gain.     

Torque sensorless control in multidegree-of-freedom manipulator

A torque sensorless control for a multi-degree-of-freedom manipulator is described. In the method, two disturbance observers are applied to each joint. One is used to realize a robust motion controller. The other is used to obtain a sensorless torque controller. A robust acceleration controller based on the disturbance observer is shown. To obtain the sensorless torque control, it is necessary to calculate the reaction torque when the mechanical system performs a force task. The calculation method for the reaction torque is explained. Then the method is expanded to workspace force control in the multi-degree-of-freedom manipulator. Several experimental results are shown to confirm the validity of the proposed sensorless force controller     

A rotor position and speed observer for permanent-magnet motors with nonsinusoidal EMF waveform

A new nonlinear reduced-order observer to estimate the rotor speed and position for permanent-magnet motors, with arbitrary electromotive force (EMF) waveform, is presented. The proposed observer is suitable for the realization of a torque control with minimum torque ripple. In order to implement the observer, the EMF generated by the motor is first obtained experimentally offline. After that, it is approximated by a Fourier series in order to develop the model to be used in the online estimation. From the estimated EMF, rotor position and speed are calculated using the relationship between the EMF and the rotor variables. The proposal is validated with experimental results.     

State estimation on flexible robots using accelerometers and angular rate sensors

Fast moving robots with elastic joints and/or elastic links require vibration suppression to achieve accuracy. We introduce a two-degrees-of-freedom control scheme (2DoF) consisting of a feedforward component based on the flatness approach and a classic feedback component, such as a PD motor joint control with additional link position error or joint torque error feedback. Such a control scheme requires knowledge of the full system state. We present an approach for state estimation using angular rate-and acceleration-sensors-mounted on each robot link-that can be used for any kind of elastic robot manipulator. We validate our theory by measuring a very fast trajectory and the influence of an external disturbance on an articulated robot with two flexible links and three joints.     

Identification of dynamic and friction parameters of a parallel manipulator with actuation redundancy

The dynamic model is formulated in the joint space for a parallel manipulator with actuation redundancy. The established model is expressed in its linear matrix form with respect to the dynamic and friction parameters, and then the Weighted Least Square (WLS) method is applied to estimate the parameters. In order to get satisfying estimated results, the filters of joint angle and actuated torque are designed for the parallel manipulator. A simple and effective method is presented to design the excitation trajectory by analyzing the mechanism structure characteristics of the actual parallel manipulator. Another type of trajectory which is different from the excitation trajectory is adopted to verify the estimated parameters. The dynamic control experiments based on the identified model with the estimated parameters are implemented on an actual 2-DOF parallel manipulator with actuation redundancy, and the tracking accuracy of the identified model is compared with the result of the so-called nominal model.     

MEMS IMU Based Pedestrian Indoor Navigation for Smart Glass

In open air environment, Global Positioning System (GPS) receiver can determine its position with very high accuracy. Inside a building the GPS signal is degraded, the position estimation from the GPS receiver is very erroneous and of no practical use. In this paper, we present an indoor navigation system to track the position of a pedestrian by using built-in inertial measurement unit (IMU) sensors of a smart eyeglass. The device used for this project was an intelligent eye-wear “JINS MEME”. Here algorithm for step detection, heading and stride estimation are used to estimate the position based on the known locations of the walker using Pedestrian Dead Reckoning method (PDR). We have used extended Kalman filters as sensor fusion algorithm, where measurements of acceleration and orientation from IMU are used to track user’s movement, pace, and heading. The results showed that the level of accuracy was entirely acceptable. Average deviancy between the estimated and real position was less than 1.5 m for short range of walk was accomplished. There are some ideas for further development. Increasing the accuracy of the position estimation by palliation of stride length estimation error was identified as the most essential.     

Position/force control of uncertain constrained flexible joint robots

This paper addresses the issue of adaptive position/force control of uncertain constrained flexible joint robots (FJRs). The controller is developed without the assumptions of weak robot joint flexibility as adopted in popular singular perturbation (SP) approaches. It relies on the feedback of joint state variables and avoids noisy joint torque measurements found in most controllers developed so far. In addition to the robot inertia parameters, the joint stiffness and the motor inertia are also assumed to be unknown. The proposed approach achieves the position tracking and the boundedness of force errors. The simulation study is conducted to verify the effectiveness of the approach.     

A wireless reconfigurable modular manipulator and its control system

As the core of Industry 4.0, the intelligent manufacturing technology requires robotic arms to be networked, customized and flexible. Traditional industrial robots have a large number of electrical cables. The end effectors cannot be easily replaced. In this paper, a reconfigurable modular arm with quick replacement of tools and its neural adaptive control system are developed. It consists of an anthropomorphic 7 degree-of-freedom (DOF) manipulator, a reconfigurable connection mechanism (RCM) and a wireless controller. Based on the modular design ideas, each joint is integrated with a motor, a harmonic reducer, two encoders and a servo controller to achieve high torque capacity but keep light weight. Shape Memory Alloy (SMA) wires and steel spheres are used in the RCM to provide mechanical and electrical connections between the arm and the end effector for rapid replacement. The central controller communicates with each servo controller through wireless communication links. Furthermore, the neural adaptive control method compensating position and force tracking errors caused by the model uncertainty and time delay is addressed. Finally, the prototype is fabricated and experiments are carried out. The developed arm has high position accuracy, force control accuracy, and reliable reconfigurable capability.     

Relating agonist-antagonist electromyograms to joint torque duringisometric, quasi-isotonic, nonfatiguing contractions

Describes an experimental study which relates simultaneous elbow flexor-extensor electromyogram (EMG) amplitude to joint torque. Investigation was limited to the case of isometric, quasi-isotonic (slowly force-varying), nonfatiguing contractions. For each of the flexor and extensor muscle groups, the model relationship between muscle group torque contribution and EMG amplitude was constrained to be a sum of basis functions which had a linear dependence on a set of fit parameters. With these constraints, the problem of identifying the EMG-to-torque relationship was reduced to a linear least squares problem. Surface EMGs from elbow flexors and extensors, and joint torque were simultaneously recorded for nonfatiguing, quasi-isotonic, isometric contractions spanning 0-50% maximum voluntary contraction. Single-/multiple-channel unwhitened/whitened/adaptively-whitened EMG amplitude processors were used to identify an EMG-to-torque relation, and then estimate joint torque based on this relation. Each unwhitened multiple-channel EMG-to-torque estimator had a standard error (SE) approximately 70% of its respective single-channel estimator. The adaptively whitened multiple-channel joint torque estimator had an SE approximately 90% of the unwhitened multiple-channel estimator, providing an estimation error ≈3% of the combined flexion/extension torque range. The experimental studies demonstrated that higher fidelity EMG amplitude processing led to improved joint torque estimation     

Maximum likelihood localization of 2-D patterns in the Gauss-Laguerre transform domain: theoretic framework and preliminary results

Usual approaches to localization, i.e., joint estimation of position, orientation and scale of a bidimensional pattern employ suboptimum techniques based on invariant signatures, which allow for position estimation independent of scale and orientation. In this paper a Maximum Likelihood method for pattern localization working in the Gauss-Laguerre Transform (GLT) domain is presented. The GLT is based on an orthogonal family of Circular Harmonic Functions with specific radial profiles, which permits optimum joint estimation of position and scale/rotation parameters looking at the maxima of a "Gauss-Laguerre Likelihood Map." The Fisher information matrix for any given pattern is given and the theoretical asymptotic accuracy of the parameter estimates is calculated through the Cramer Rao Lower Bound. Application of the ML estimation method is discussed and an example is provided.     

Design and implementation of sensorless techniques for switched reluctance drive systems

This article proposes two different methods for estimating the shaft position for a switched reluctance motor (SRM). Method 1 uses the self-inductance estimation technique to obtain the rotor position. First, by on-line measuring the slope of the stator current and compensating for the back electromotive force (EMF) effect, the self-inductance of the SRM can be detected. Then, the shaft position of the motor can be estimated according to the self-inductance. Method 2, on the other hand, uses the phase-locked loop technique to generate high-frequency signals. These signals can be used to estimate the shaft position of the SRM. The two proposed methods are compared and discussed in the article. Several experimental results are shown to validate the theoretical analysis. The adjustable speed range of the system is from 10 to 3000 rpm. Additionally, the proposed drive system can automatically start from a standstill to a setting speed.