Nowadays, industrial servopositioning systems are used in many applications that demand high positioning accuracy, while requiring at the same time high dynamic movements. However, these systems often suffer from mechanical non-idealities, primarily the elasticity induced by the trasmission, which leads to load oscillation when using a standard collocated controller approach. While load side position sensors can be added to allow the use of control strategies that reduce the vibrations, this solution is often impractical in industrial environment. In this paper, we propose the use of the Acceleration Aided Kalman Filter (AAKF), which requires a low-cost load side MEMS accelerometer, to obtain accurate and robust estimates of load variables. Using load side information, two different control approaches are implemented, a PID with Active Damping and a Model Predictive Controller (MPC). The experimental results confirm that both control algorithms work as intended, considerably reducing load side vibration while using high dynamic movements, therefore reducing the cycle time of the positioning. Thus, the AAKF is validated as an effective alternative to the standard load position sensor in industrial environment.

This paper presents development of a 2DOF haptic feedback control stick for remote control of a two-parallel-wheeled rover. In bilateral control, when dynamics are quite different between a leader and follower devices, e.g., between a linear-slider type of control stick and a wheel with a comparatively large moment of inertia, a force reproduced on the control stick based on external forces applied to the rover’s wheel, is disturbed largely. Since the position control forces the control stick’s position and the rover’s angular velocity to be synchronized, the operator feels not only the reproduced force but also a force by this position control inevitably on the same time. We call this force a restoring force. The restoring force disturbs the operator to feel the reproduced force accurately. But the authors think the restoring force is meaningful for remote navigation of the rover as another haptic information. Thus, in this paper, we developed a 2-DOF haptic control stick, which transfers the reproduced force and the restoring force separately to a slider and a grip, and proposed a control method for achieving this purpose. The control stick was implemented and was performed successfully in verification experiments using the proposed control method. Experimental results were discussed comparing to the former 1-DOF control stick.

High accuracy motion control is a subtle subject, and many critical aspects are related to the non-idealities of both the actuators and the mechanical device to be moved. Based on the multi-year experience gained in a hands-on laboratory, involving tens of Mechatronics’ master students at the University of Padova, it has been possible to set up (in a Matlab/Simulink environment) a realistic simulator of a servo positioner, accounting for most of the characteristics of an actual system. The typical laboratory experience starts with the identification of the relevant physical parameters of the system to be controlled (each student receives a different encrypted model of the system to be controlled), followed by the design of controllers and disturbance observers in a deterministic setting. Then, a stochastic approach is applied, with the design and experimental tuning of a Kalman filter. To improve the tracking and disturbance rejection of the controlled system, it is also studied the application of advanced techniques like Repetitive Control, Zero-Phase Tracking Error Control, Iterative Learning Control. As a result, it has been possible to get the full involvement of each student even in Covid-19 time, with results that closely matched those obtained in the previous hands-on experience.

The precise and reliable interaction force knowledge is among the main aspects of human-robot interaction applications. Since many robots are equipped with joint torque sensors, relying on these measurements avoids increasing cost and complexity, brought by additional sensors. In this paper, we investigate the sensing capabilities of the Franka Emika Panda Robot for interaction force estimation, focusing on the available filtered force estimates provided by the robot controller. We perform experiments involving contact interaction between the robot and an external environment, implemented by using an impedance controlled servomotor. In this way, it is possible to reproduce forces typical of the human behaviour, in controlled and repeatable conditions. The evaluation is based on the identification of the motor impedance parameters, comparing the results obtained by the Panda interaction force estimate with a ground truth value, obtained by load cell measurements. Since joint torque measurements are heavily affected by disturbance torques (e.g. friction) a simple compensation procedure is performed, through data collected without contact. The delay introduced on the external force measurements by the filtering action is compensated, allowing an online usage of the proposed method. Results show that the Panda Robot provides a fairly good estimate of the interaction force.

Low frequency dynamic force offsets and measurement noises make utilization of force sensor signal a difficult task, especially, the direct feedback of force measurements in force control systems. To solve these force sensor problems, a novel Kalman filter-based force observer that automatically estimates and eliminates force sensor offsets and attenuates measurement noises is developed in this paper. A dynamic model of force sensing system is derived taking into consideration the dynamic interaction among the motor, the load, and the force sensor between them, as well as the measurement equations. The state-space representation of dynamic force offsets is formulated and augmented to the system dynamic equations from which a state-space Kalman filter is designed. The properties of the designed Kalman filter are further theoretically analyzed in the transfer function form. To verify its effectiveness, experiments are carried out where performance comparison is made to that of a conventional Kalman filter. The proposed observer is found to perform better than the conventional one. Moreover, the transfer function form exhibits a simple structure which makes it simple to implement.

A bilateral control system permits to an operator to perform a task manipulating a master robot while a slave robot executes the actual operation: the controller mirrors the position, speed and external forces between the two robots, thus mimicking the law of action-and-reaction and providing haptic feedback to the operator. Based on the bilateral control, a Motion Copying System permits to record the operator task by saving the master position, speed and applied force, that can be then used to replay the movement. However, the recorded task is rigid with respect to environmental changes and requires that the operator records a new task every time the surrounding environmental conditions vary. In this work, a method for motion imitation is investigated, with the objective of learning a generalized movement that can be easily adapted for a different task without the need for operator intervention.

Teleoperation technology is widely employed in the fields of industry and human support. Bilateral control, which is one of the possible methods to achieve teleoperation, enables mutual transmission of operational force of an operator and reaction force from remote environment. However, teleoperation often involves non negligible communication delays, due to the limits of the communication networks. As a countermeasure against communication delays, bilateral control using a force-control-based communication delay compensation has been proposed. This approach is effective in stabilizing system behavior and in maintaining the force states, so that operator's operational force and reaction force from environment can act in pairs and opposite direction, even during contact tasks. In this paper, we introduce a bilateral control that makes use of a force-control-based communication delay compensation, with a new control structure in which structural redundancy of conventional system is removed. The proposed bilateral control system demonstrates through experiments a stable teleoperation and an accurate force matching performance through experiments.

For fast and precise motion control, the robustness against disturbances and/or system uncertainties is one of essential factors. In many industrial applications, there is a typical situation that the non-collocated mass position can not be measured because of cost limitations and/or manufacturing issues. The robustness and the control performance usually deteriorates compared to the case that all state variables are measurable. To solve this problem, the acceleration-aided Kalman filter (aaKF) using a MEMS accelerometer has been proposed. In this paper, the robustness improvement by the aaKF is analyzed based on the idea of loop transfer recovery. Analysis and simulation results show that reliable measurements of load-side acceleration improve the estimation of load-side information and the robustness of the control system implementing an optimal feedback. The utility of the aaKF in a two-mass system is confirmed from experiments.

Mobile robots path planning is a central problem in every situation where human intervention is not desired or not possible to accept: full automated industrial warehouses or general stocking areas and every domestic application that involves a mobile robot and special cases where environment is prohibited for human accessing like toxic wastes and bombs defusing [1]. Currently, neural networks are applied to problems related to mobile robot navigation. However, they are not as popular as in applications like image processing, speech recognition or machine translation, where they are commercially relevant. In this paper we propose a Long Short-Term Memory (LSTM) neural network as an online search agent to tackle the problem of mobile robots path planning in unknown environments, meaning that the agent relies only on local map awareness realized with a LRF sensor and relative information between robot and goal position. Specifically, a final structure of LSTM network is analyzed and its performance is compared with the A* algorithm, a widely known method that follows the best-first search approach. Subsequently, an analysis of the method developed on a real robot is described.

This paper describes the design of a control strategy for robotic rehabilitation devices, aimed at recovering the motor skills of patients affected by particular diseases that damage the neuromuscular apparatus of the human body. There are two different but related activities in the project here described. At first, a non-linear parameter identification procedure, based on the Recursive Least Square (RLS) method, has been used to identify the impedance at the end-point of the human arm. To obtain more accurate estimation values, the RLS algorithm uses the state values (position and velocity) provided by a state observer based on acceleration-aided Kalman Filter (aaKF). Then, the design of a Non-Linear Adaptive Controller (based on the arm's characteristic) is described. The controller aims at helping the patient during the rehabilitation exercises, by using a level of assistance that varies according to the patient's performance. In this way it is possible to emulate the help of the physiotherapist, teaching the patient the correct execution of the exercise only if necessary, thus implementing an assist-as-needed policy.

In-circuit tests play a key role in manufacturing electronic devices with a high level of reliability. One of the most flexible technology for the tests is based on flying probes, in which a set of conductive needles is automatically positioned on multiple test points of the device under test. The probes are controlled at high speed within the working space, to increase the production rate, Position and contact force of probing system should be accurately controlled, to prevent damages to the parts. A force sensor is usually used in the contact detection and for controlling the contact force. However, the force sensor is weak against impact force and expensive. A Reaction Force Observer (RFOB) is often used in force control system without force sensors. This paper proposes a fast force controller for probing systems without force sensor. In this study, a MEMS accelerometer is used to improve the performance of the RFOB. Acceleration-aided Kalman Filter (aaKF) is combined with the RFOB to derive accurate estimates of the velocity and acceleration signals. The contact detection is conducted using jerk signal, which can be obtained by differentiating the acceleration. After the contact detection, a negative constant force is applied for a short period, to decelerate the motion of the probe. Finally, a force control is applied. Experiments were conducted to validate the effectiveness of the proposal. As a result, the proposed method can quickly control the contact force without overshoot, with a settling time of 10 ms. The proposed control is effective for circuit probing systems, because the force is controlled in short time, so making the in-circuit test time short.

Haptic devices are now being deployed in several applications. One of the most interesting is the bilateral telerobotics, as such devices can provide a vivid tactile and/or proprioceptive rendering of the remote environment. In order to make this type of devices more affordable, low cost technology is going to be used, with a possible reduction in performance, due to the loss of backdriveability, especially when sensorless force control is implemented. The use of Reaction Force Observers (RFOB) can ameliorate the overall performance, but such solution achieves a good performance only when an accurate model of the electromechenical system is available. This paper proposes the use of an Acceleration-aided Kalman Filter (aaKF) to implement an accurate identification of the mechanical parameters of the haptic device. Experimental results show how the aaKF-based RFOB, with a properly designed identification procedure of the non-linear friction parameters, can match in performance a force control with an actual force sensor.

Several technological solutions have ben recently proposed for fingers rehabilitation in patients who were affected by a stroke, in particular for those who cannot generate the finger force but with preserved sEMG signals. In fact, a very promising approach uses a robot rehabilitation system controlled through sEMG signals. However, this system has two main problems: 1) the placement of electrodes is made manually and this could bring to a non-optimal detection of signals; 2) the cost of treatments is very high, mainly due to the usage of single-use, dispodsable electrodes. Our proposal is to use a robot rehabilitation system with a low-cost armband instead of standard electrodes. The armband has 8 sEMG sensors and a 9-DoF inertial sensor, it has electrically safe setup with low voltage battery and Bluetooth protocol. Moreover it is a very low cost and reusable equipment. The validity of the proposal was confirmed through experiments.

In many industrial applications, servo-positioning devices are composed of an electric motor, connected to the mechanical load through elastic elements. The problem of two-mass resonant systems has been studied for long time, and the main issue targeted has been the development of accurate and robust servo positioning devices, without making use of a load-side position sensor. Indeed, by using properly designed observers, it is possible to obtain accurate information on the load position, but the robustness of control laws based on this solution is known to be rather weak. In this paper, we explore the feasibility, the performance and the robustness of a an optimal feedback control, in which the full state of the system is obtained by a Kalman Filter (KF), which process not only the position measurement of the motor, but also the acceleration measurement of the load, obtained by using a low-cost MEMS sensor. The experimental results confirm that by using this additional sensor, the robustness of the control is greatly improved, thanks to the higher accuracy of the estimate of the load side variables.

This paper deals with a master-slave robotic system with haptic feedback that has been recently proposed by the authors for supporting the clinician during the execution of immerse ultrasound examinations. The focus is on providing additional details on how to tune the force feedback controller, in order to guarantee stability of the overall control system. After arguing the stability conditions by exploiting an approach based on the small gain theorem, a controller tuning procedure based on the identification of the human impedance parameters is proposed.

This paper presents a use of MEMS accelerometers for performance improvement of motion control systems equipped with low resolution position sensors. It is well-known that control performance depends on hardware performance such as a sensor resolution and a computational power. Above all, the use of low resolution sensors restricts the achievable enhancements on the control bandwidth, due to quantization noise. In this paper it is proposed to overcome such limitation by using a Kalman estimator, utilizing the measurements provided by a low cost MEMS accelerometer in the estimation of position information. Moreover, the same measurement is used for the acceleration based disturbance observer (a-DOB), where no differentiator is needed to estimate the disturbance, so that a better estimation capability and positioning performance can be achieved. The effectiveness of the proposed control system has been verified by several experiments using a prototype of a table system.

Several time delay compensation methods for teleoperation systems have been researched for a long time (e.g. Smith predictors, communication disturbance observers, etc). Based on the communication disturbance observer, the authors have proposed a vibration suppression scheme for resonant systems, based on reflected wave rejection and a wave compensator. From this method, it is found that vibration in resonant system can be suppressed by making use of a time delay compensation method and it is observed that a reflected wave induces vibrations. Taking a dual approach, this paper proposes a time delay compensation method, based on our previously developed reflected wave rejection, used for the vibration suppression in the resonant system. Firstly, a wave representation of time delay system is derived and an equivalence of wave and time delay systems is clarified. It is also clarified that a cause of vibration in the time delay system is a reflected wave as well as in a resonant system. Finally, it is shown how the reflected wave rejection can be seems as a time delay compensation method, to be used in time delay systems. The validity of the proposed method is verified by the experimental results.

Recently, a telerobotic equipment has been proposed for the assistance of the human operators, during the execution of immerse ultrasound examinations. This is usually a difficult task, as the ultrasound probe must be held at some distance from the surface to be scanned, and the distance perceived by the human eye can be affected by the optical distortion produced by the liquid. Additionally, the operator must devote all her/his attention to the ultrasound images, then the visual control of the operation would be quite annoying. Automated placement of the probe, on the other hand, may lead to unsatisfactory results and a fine, operator-driven trimming may be required to obtain the best ultrasound image. Therefore, a master/slave system with haptic feedback has been proposed as a novel solution to assist the clinician to achieve an optimal positioning of the probe while performing an immerse ultrasound examination. Being a non-contact task, a custom proximity sensor is used to estimate both the distance and orientation of the probe from the surface to be scanned. Such information is used both to control the probe orientation and to generate a feedback force at the master side, which simulates the presence of a virtual constraint, with a user-defined mechanical impedance, located above the object surface. This paper, after describing the overall system, addresses the study of the stability of the proposed teleoperator during surface following.

In a research field of network-based control systems (NBCSs), the time delay problem is one of the most significant issues. Efficient stabilization methods of time delayed control systems enable NBCSs to be flexibly applied to many kinds of situations. A novel time delay compensation method based on the concept of network disturbance (ND) and communication disturbance observer (CDOB) has been proposed. The compensation method has the same effectiveness as that of the Smith predictor. In addition, since the method is simple and does not need time delay model or time delay measurement, it can be easily implemented to various applications. However, the design method has not been concerned so far. This paper therefore presents stability analysis and studies a practical design procedure of the time delayed control systems with CDOB. At first, the concept of ND is introduced and the validity of the time delay compensation method is described. Then an analysis about the effects of parameters in control systems on stability is conducted. Characteristics of the effects of parameters on stability come out. Then we study a practical design procedure of the time delayed control systems. The validity of the design procedure is validated by experimental results. In the experiment, we also verify the performance of the system in the case of time-varying delay. Finally, comparative study of the method to the Smith predictor is presented.

An ever-growing number of Internet-connected devices are now accessible to a multitude of users. Being an ubiquitous communication means, the Internet could enable any user to reach and command any device connected to the network. This paper reports the successful application of real-time closed-loop control over the Internet in the Java-Based Interface for Telerobotics (JBIT) system, in which the Internet users can access and command a two-degrees-of-freedom robot in real time, receiving both visual and force feedback. When closed-loop control of a remote system comes into play, careful evaluation of the performance and limits of the communication system in use is mandatory. The reported analysis shows that the main Internet limits are unknown available throughput, variable delay, and loss of some data packets, in particular when the network is congested. Once the limits of the communication system are known, it is shown that it is possible to use the Internet for the remote closed-loop control of a slave robot, provided that suitable strategies to guarantee operability and safety of the controlled system are implemented. Such strategies are concerned with on-line identification of the connection characteristics, adaptation of the data rate to the available throughput, recovery of the missing packet, and handling of the variable delay. Moreover, visual feedback dataflow shares the same Internet connection with the real-time control data. To prevent congestion, new tools for adaptive dataflow management have been developed. Finally, an improved coordinating force control scheme, aimed at enhancing the transparency of the teleoperator, is presented.