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Sensorless passive lead-through programming (LTP) is a promising physical human-robot interaction technology that enables manual trajectory demonstrations based on gravity and friction compensation. The major difficulty lies in static friction compensation during LTP start-up. Instead of static friction compensation, conventional methods only compensate for Coulomb friction after the joint velocity exceeds a threshold. Therefore, conventional start-up external torques must overcome static friction. When the static friction is considerable, it is difficult for conventional LTP to start up and make small movements. This paper aims to decrease the start-up external torque and improve the small movement performance.

This paper reveals a novel usage of a high-gain position-loop in industrial robot applications aimed at sensitively detecting external torque during start-up. Then, the static friction is partly compensated by Coulomb friction to facilitate start-up. In addition, a detailed transition method between the proposed start-up and conventional passive LTP is proposed based on a finite state machine.

Experiments are implemented on the ROKAE XB4 robot to verify the effectiveness of the proposed external torque detection. Compared with the conventional LTP method, the proposed LTP method significantly decreases the start-up external torque and facilitates small movements.

This paper proposes and verifies a novel start-up method of sensorless LTP based on a start-up external torque detection and a transition method between start-up and conventional LTP. This research improves the LTP start-up performance, especially for industrial robots with large static friction.

The aim of this paper is to implement direct teaching of industrial manipulators using current sensors. The traditional way to implement teaching is either to use a teaching pedant, which is time consuming, or use force sensors, which increases system cost. To overcome these disadvantages, a novel method is explored in the paper by using current sensors installed at joints as torque observers.

The method uses current sensors installed at each joint of a manipulator as torque observers and estimates external forces from differences between joint-driven torque computed based on the values of current sensors and commanded values of motor-driven torque. The joint-driven torque is computed by cancelling out both pre-calibrated gravity and friction resistance (compensation). Also, to make the method robust, the paper presents a strategy to detect unexpected slowly drifts and zero external forces and stop the robot in those situations.

Experimental results demonstrated that compensating the joint torques using both pre-calibrated gravity and friction resistance has performance comparable to a force sensor installed on the end effector of a manipulator. It is possible to implement satisfying direct teaching without using force sensors on 7 degree of freedom manipulators with large mass and friction resistance.

The main contribution of the paper is that the authors cancel out both pre-calibrated gravity and friction resistance to improve the direct teaching using only current sensors; they develop methods to avoid unsafe situations like slow drifts. The method will benefit industrial manipulators, especially those with large mass and friction resistance, to realize flexible and reliable direct teaching.

This paper aims to propose a forcefree control algorithm that is based on a dynamic model with full torque compensation is proposed to improve the compliance and flexibility of the direct teaching of cooperative robots.

Dynamic parameters identification is performed first to obtain an accurate dynamic model. The identification process is divided into two steps to reduce the complexity of trajectory simplification, and each step contains two excitation trajectories for higher identification precision. A nonlinear friction model that considers the angular displacement and angular velocity of joints is proposed as a secondary compensation for identification. A torque compensation algorithm that is based on the Hogan impedance model is proposed, and the torque obtained by an impedance equation is regarded as the command torque, which can be adjusted. The compensatory torque, including gravity torque, inertia torque, friction torque and Coriolis torque, is added to the compensation to improve the effect of forcefree control.

The model improves the total accuracy of the dynamic model by approximately 20% after compensation. Compared with the traditional method, the results prove that the forcefree control algorithm can effectively reduce the drag force approximately 50% for direct teaching and realize a flexible and smooth drag.

The entire algorithm is verified by the laboratory-developed six degrees-of-freedom cooperative robot, and it can be applied to other robots as well.

A full torque compensation is performed after parameters identification, and a more accurate forcefree control is guaranteed. This allows the cooperative robot to be dragged more smoothly without external sensors.

The purpose of this paper is to design a practical direct teaching method for the industrial robot with large friction resistance and gravity torque but without expensive force/torque sensor, where the gravity torque is just a function of joints position, whereas the friction is closely associated with joint velocity, temperature and load.

In the teaching method, the output torque of joint motor is controlled through current to compensate gravity torque completely and friction resistance incompletely. Three variables closely associated with friction are investigated separately by experiment and theoretical analysis, and then a comprehensive friction model which is used to calculate the required compensated friction torque is proposed. Finally, a SIASUN 7 degrees of freedom robot was used to verify the model and the method.

Experimental results demonstrated that the teaching method enables an operator to teach the robot in joint space by applying small force and torque on either end-effector or its body. The friction investigation suggests that the velocity and temperature have a strong nonlinear influence on viscous friction, whereas load torque significantly influences the Coulomb friction linearly and causes a slight Stribeck effect.

The main contribution includes the following: a practical joint space direct teaching method for a common industrial robot is developed, and a friction model capturing velocity, temperature and load for robot joints equipped with commercialized motors and harmonic drives is proposed.

The purpose of this paper is to present a direct force control which uses two closed-loop controller for one-degree-of-freedom human-machine system to synchronize the human position and machine position, and minimize the human-machine force. In addition, the friction is compensated to promote the performance of the human-machine system.

The dynamic of the human-machine system is mathematically modeled. The control strategy is designed using two closed-loop controllers, including a PID controller and a PI controller. The frictions, which exist in the rotary joint and the hydraulic wall, are compensated separately using the Friedland’s observer and Dahl’s observer.

When human-machine system moves at low velocity, there exists a significant amount of static friction that hinders the system movements. The simulation results show that the system gives a better performance in human-machine position synchronization and human-machine force minimization when the friction is compensated.

The acquired results are based on simulation not experiment.

This paper is the first to apply the electrohydraulic servo systems to both actuate the human-machine system, and use the direct force control strategy consisting of two closed-loop controllers. It is also the first to compensate the friction both in the robot joint and hydraulic wall.

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

The sensorless external force estimation of robot manipulator can be helpful for reducing the cost and complexity of the robot system. However, the complex friction phenomenon of the robot joint and uncertainty of robot model and signal noise significantly decrease the estimation accuracy. This study aims to investigate the friction modeling and the noise rejection of the external force estimation.

A LuGre-linear-hybrid (LuGre-L) friction model that combines the dynamic friction characteristics of the robot joint and static friction of the drive motor is proposed to improve the modeling accuracy of robot friction. The square root cubature Kalman filter (SCKF) is improved by integrating a Sage Window outer layer and a nonlinear disturbance observer (NDOB) inner layer. In the outer layer, Sage Window is integrated in the square root Kalman filter (W-SCKF) to dynamically adjust noise statistics. NDOB is applied as the inner layer of W-SCKF (NDOB-WSCKF) to obtain the uncertain state variables of the state model.

A peg-in-hole contact experiment conducted on a real robot demonstrates that the average accuracy of the estimated joint torque based on LuGre-L is improved by 4.9% in contrast to the LuGre model. Based on the proposed NDOB-WSCKF, the average estimation accuracy of the external joint torque can reach up to 92.1%, which is improved by 4%–15.3% in contrast to other estimation methods (SCKF and NDOB).

A LuGre-L friction model is proposed to handle the coupling of static and dynamic friction characteristics for the robot manipulator. An improved SCKF is applied to estimate the external force of the robot manipulator. To improve the noise rejection ability of the estimation method and make it more resistant to unmodeled state variable, SCKF is improved by integrating a Sage Window and NDOB, and a NDOB-WSCKF external force estimator is developed. Validation results demonstrate that the accuracy of the robot dynamics model and the estimated external force is improved by the proposed method.

The purpose of this paper is to find a simple structure of motion controller for permanent magnet direct drive. Application of sliding mode controller theory and equivalent disturbance estimator creates proper non‐linear characteristics, which ensures controller robustness against friction.

The position and speed controller is based on robust design methodology introduced by a sliding mode technique. The paper proposes a combination of sliding mode controller and proportional integral (PI) equivalent disturbance estimator. The friction model is Coulomb friction with a large static friction effect. The double boundary layer is used to compensate the effect of stiction. The synthesis is performed using simulation techniques and subsequently the behaviour of a laboratory speed control system is validated in the experimental setup. The control algorithms of the system are performed by a microprocessor floating point DSP control system.

The proposed sliding mode controller structure with equivalent disturbance estimator guarantees expected robustness against friction. Experimental results show that the control approach can decrease the tracking error, enhance the system's robustness and attenuate high‐frequency chattering in the control signal.

The proposed controller was tested on a single machine under well‐defined conditions. Further investigations are required before any industrial applications.

The proposed controller synthesis and its results may be very helpful in robotic systems where non‐linear friction is a characteristic for many industrial robots and manipulators.

The method of sliding mode controller synthesis was proposed and validated by simulation and experimental investigations.

Flight simulators are one of the noticeable breakthroughs in aerospace engineering. One of the main compartments of flight simulators is its control loading system (CLS). The CLS functions as a generator of virtual aerodynamic control-loads over control columns of a simulator. This paper aims to present the design of a high-fidelity six six degrees of freedom (6DOF) nonlinear CLS for the Boeing-747 aircraft simulator.

An introduction to CLS for flight motion simulators are first recapitulated. Afterward, the commanding devices are explained through schematics available in an engineering sense. This paper then presents in detail, the active control loading strategy and hardware design for the CLS, while also introducing the aerodynamic model structure. The satisfactory computer numerical simulations are presented before the paper ends up in concluding remarks.

The multiple input multiple output (MIMO) 6DOF nonlinear CLS for Boeing-747 flight simulator has been successfully developed. The outcome of computer simulations in real-time verifies practicality of the design strategy. The research presented in this paper could be a simple roadmap for prototyping high-fidelity 6DOF nonlinear CLS for flight motion simulators.

The available control architecture and hardware technologies cannot enable a high-fidelity load realization in a CLS. The existing research has not yet presented a 6DOF nonlinear MIMO CLS architecture along with the underlying controller setup for a high-fidelity load realization. In this paper, the design of a high-fidelity 6DOF nonlinear MIMO CLS for flight simulator of a large transport aircraft has been accomplished.