Electroadhesive clutches have attracted a great deal of interest in the last decade as semi-active actuators for human-robot interaction due to their lightweight, low power consumption, and tunable high-torque output capability. However, because of the complexity of their dynamics, in most cases, they are utilized in an ON/OFF -control strategy. In this regard, the non-autonomous (time-dependent) degradation of electroadhesive behavior is an inherent challenge that injects unpredictability and uncertainty into the behavior of this family of semi-active clutches. We propose a novel approach to preventing degradation of electroadhesion using a segmented electrode design that modulates the electrical field on the dielectric surface while using a direct current signal and securing low power consumption. This paper, for the first time, presents an optimization process based on a novel analytic model of the proposed actuator. It also develops a data-driven model augmentation using a hybrid shallow learning approach composed of a long short-term memory (LSTM) architecture which is combined with the analytical model. The performance of the proposed semi-active clutch and the data-driven hybrid model is experimentally validated in this paper.

Bilateral telerobotic systems have attracted a great deal of interest during the last two decades. The major challenges in this field are the transparency and stability of remote force rendering, which are affected by network delays causing asynchrony between the actions and the corresponding reactions. In addition, the overactivation of stabilizers further degrades the fidelity of the rendered force field. In this article, a real-time frequency-based delay compensation approach is proposed to maximize transparency while reducing the activation of the stabilization layer. The algorithm uses a regulated bound-limited multiple Fourier linear combiner to extract the dominant frequency of force waves. The estimated weights are used in conjunction with the relatively phase-lead harmonic kernels to reconstruct the signal and generate a compensated wave to reduce the effect of the delay. The reconstructed force will then pass through a modulated time-domain passivity controller to guarantee the stability of the system. We will show that the proposed technique will reduce the force-tracking error by 40% and the activation of the stabilizer by 79%. It is shown, for the first time, that through the utilization of online adaptive frequency-based prediction, the asynchrony between transmitted waves through delayednetworks can be significantly mitigated while stability can be guaranteed with less activation of the stabilization layer.

In this paper, we aim to solve inverse kinematics of the integrated robotic arm-hand systems to achieve precision grasping, provided the desired grasp configuration (contact points + contact normals). The key insights of our approach are three-fold. First, we propose a human-inspired thumb-first strategy and consider one finger of the robotic hand as the "thumb" to narrow down the search space and increase the success rate of the algorithm. Second, we formulate the arm-thumb serial chain as a closed chain while other fingers are still as serial chains such that the entire arm-hand system is controlled as a hybrid parallel-serial system. The closed-chain formulation truncates and simplifies the task hierarchy of the entire arm-hand system. Third, we attach a virtual revolute joint to the thumb’s tip with its rotation axis aligning with the thumb’s contact normal to allow this virtual joint to act as the embodiment of the thumb’s functional redundancy. By selecting the thumb’s joints including the virtual revolute joint as the active joints of the arm-thumb closed chain, the arm-thumb system’s self-motion (i.e., the palm pose) and the thumb’s functional redundancy can be directly controlled without using the null space projection. This provides a new possibility to control the self-motion of robot manipulators. Simulation results will demonstrate the advantages and superb performance of the proposed approach for solving the problem of inverse kinematics of achieving precision grasps compared to other classical approaches based on the Damped Least-Squares method [1] in terms of the average success rate (96% v.s. 12%).

This paper presents a novel design concept of a miniaturized Magneto-Rheological (MR) clutch. The design uses a set of spur gears as a means to control the torque. MR clutches with various configurations such as disk-, drum-, and armature-based have in the past been reported in the literature. However, to the best of our knowledge, the design of a clutch with spur gears to use MR fluid in squeeze mode is a novel concept that has never been reported previously.After a brief description of the MR clutch principles, the details of the mechanical design of the spur gear MR clutch are discussed. The distribution of the magnetic flux inside the MR clutch is studied using finite element analysis in COMSOL Multiphysics software. Preliminary experimental results using a prototype MR clutch that validates the new concept and the results therein will be presented next. To clearly show the performance of the proposed design, we compared the torque capacity of our MR clutch obtained experimentally with that of a simulated disk-type MR clutch of a similar size.

This paper presents an improved design approach for the construction of a Magneto-Rheological (MR) clutch intended to be used in a prospective 5 degrees of freedom robot. The MR clutch features embedded Hall sensors for intrinsic torque control. After a brief description of the MR clutch principles, the details of the mechanical design are discussed. Simulation and preliminary experimental results demonstrate the main characteristics and advantages of the proposed MR clutch.

This paper deals with the problem of purposefully failing or yielding an object by a robotic gripper. We propose a grasp quality measure fabricated for robotic harvesting in which picking a crop from its stem is desired. The proposed metric characterizes a suitable grasp configuration for systematically controlling the failure behavior of an object to break it at the desired location while avoiding damage on other areas. Our approach is based on failure task information and gripper wrench insertion capability. Failure task definition is accomplished using failure theories. Gripper wrench insertion capability is formulated by modeling the friction between the object and gripper. A new method inspired by human pre-manipulation process is introduced to utilize gripper itself as a friction measurement device. The provided friction model is capable of handling the anisotropic behavior of materials which is the case for fruits and vegetables. The evaluation method is formulated as a quasistatic grasp problem. Additionally, the general case of both fully-actuated and under-actuated grippers are considered. As a validation of the proposed evaluation method, experimental results for failing parts using Kuka Light-Weight Robot IV robot are presented.

This paper presents the design and evaluation of a new sensorized underactuated self-adaptive finger. Our design incorporates a two degrees-of-freedom (DOF) parallel based underactuated mechanism with an embedded load cell for contact force measurement and a trimmer potentiometer to acquire the joint variables. Integration of the sensors leads to tactile feedback fidelity without compromising the finger size and complexity which results in efficient and robust functionality. The particular rounded shape of the distal phalanx and high equilibrium position enable the finger to deliver both precision and power grasps. The effectiveness of our design is verified theoretically and through experimental results demonstrating its shape adaptability, and tactile capability.

In this paper, we present a new concept for generating magnetic field in Magneto-Rheological (MR) clutches intended for safe robotic applications. The main rationale behind this concept is to divide the magnetic field generation into two parts using an electromagnetic coil and a permanent magnet. The permanent magnet generates a bias magnetic field density at the optimum working point of the MR clutch while the energized coil can add or negate the magnetic field to a desired value. The results will show clear advantages of this concept in reducing the total weight of the MR clutch, improving the torque-to-mass ratio, and reducing electrical power consumption. The proposed concept is validated using computer model of an MR clutch and Finite Element Method (FEM) is hired to compare the characteristics of the proposed MR clutch with those from conventional coil based clutch. Experimental results will be provided to further validate the advantages of the proposed new concept.

In our previous work [1], the potential benefits of Magneto-Rheological Fluid based actuators to the field of haptics were studied. Our results showed that the superior mechanical attributes of such actuators contribute to improvement of stability and transparency in haptic devices. To this end, a novel design of a small-scale MRF-based clutch, was proposed in [1]. This paper reports on the development and validation of the proposed MRF-based clutch. In addition, a closed-loop torque control strategy is presented. The feedback signal used in this control scheme comes from the magnetic field measurement and is used to compensate for the nonlinear behavior using an estimated model, based on Artificial Neural Networks (ANNs). Such a control strategy eliminates the need for torque sensors for providing feedback signals. The performance of the developed design and the effectiveness of the proposed modeling and control techniques are experimentally validated. The results clearly demonstrate that the clutch shows great potential for use in a multiple degrees-of-freedom (DOF) haptic interface for a class of medical applications.

This paper reports on the performance evaluation of Magneto-Rheological Fluid (MRF) based actuation systems when used in haptic interfaces. MRF-based actuators exhibit superior characteristics, which can significantly contribute to the transparency and stability of haptic devices. To validate this statement, a prototype two degrees-of-freedom (DoF) haptic interface is constructed. A distributed antagonistic configuration is used in order to develop the 2-DoF haptic interface based on small-scale MRF-based clutches for a class of medical applications. The developed device is compared with three conventional haptic interfaces and their stability is compared using the Virtual Wall experiment. Next, the prototype interface is incorporated in a master-slave teleoperation medical setup. Preliminary studies on the performance of the haptic interface show great potential of MRF-based actuators for integration in haptic devices for medical interventions that require safe, accurate, and stable force representation.

In recent years, Magneto-Rheological (MR) clutches have been increasingly used for realizing compliant actuation. One difficulty in using MR clutches is the existence of nonlinear hysteretic behaviors between the input current and output torque of an MR clutch. In this paper, a new closed-loop, Field-Programable-Gate-Array (FPGA) based control scheme to linearize an MR clutch's input-output relationship is presented. The feedback signal used in this control scheme is the magnetic field acquired from hall sensors within the MR clutch. The FPGA board uses this feedback signal to compensate for the nonlinear behavior of the MR clutch using an estimated model of the clutch magnetic field. The local use of an FPGA board will dramatically simplify the use of MR clutches for torque actuation. The effectiveness of the proposed technique is validated using an experimental platform that includes an MR clutch as part of a compliant actuation mechanism. The results clearly demonstrate that the use of the FPGA based closed-loop control scheme can effectively eliminate hysteretic behaviors of the MR clutch, allowing to have linear actuators with predictable behaviors.

In this paper, an optimization method for designing MR clutches is studied. The proposed method optimizes the geometrical dimensions of an MR clutch, hence its mass, for given output torque and electrical input power. The main idea behind this optimization is that the input power and output torque are two parameters that are normally known to the designer prior to the design of an MR clutch and considering these parameters in the optimization as fixed values has a practical significance. Having presented the optimization method, we compare the characteristics of three different MR clutch configurations in order to demonstrate the effectiveness of the proposed method. A comparison between the drum, single-disk and multi-disk configurations of MR clutches is performed. Using the proposed method one can select a suitable configuration as well as the geometrical dimensions for an MR clutch that best suits the requirements of each individual design.

The two main objectives in designing a haptic interface are stability and transparency. The dynamics of the actuators employed in a haptic interface have a significant effect on these goals. In this article, the potential benefits of Magneto-Rheological Fluid (MRF) based actuators to the field of haptics are discussed. Devices developed with such fluids are known to possess superior mechanical characteristics over conventional servo systems. This contributes significantly to improved stability and transparency of haptic devices. In this study, this idea is evaluated from both theoretical and experimental points of view. First, the properties of such actuators which motivated this research are discussed. Next, two single degrees-of-freedom (DOF) haptic interfaces are used in a virtual wall experiment. These devices take advantage of an MRF-based clutch and a brushless DC motor at their core, respectively. The results of both devices are compared and show the superiority of the MRF-based clutch. In addition, design and analysis of a small-scale MRF-based clutch, suitable for a multi-DOF haptic interface, is given and its torque capacity, inertia, and mass are compared with those of conventional servo systems. Conclusions drawn from this investigation indicate that MRF clutch actuation approaches can indeed be developed to design haptic interfaces with improved stability and transparency.

In our previous work we have introduced the Distributed Active/Semi-Active actuation concept. This paper presents the design of a novel three Degrees-of-Freedom (DOF) robot manipulator based on the DASA actuation approach. The robot is developed as a proof-of-concept prototype intended to demonstrate the capacity of the DASA approach to achieve a high degree of interaction safety as well as performance. Magneto-Rheological (MR) clutches form the basis of the Semi-active actuation component, while a unidirectional motor provides the active drive for the robot. An antagonistic clutch configuration is implemented at the joints to achieve bi-directional actuation without reversal of the motor. MR clutches have been shown to exhibit excellent torque-to-inertia and torque-to-mass ratios making them likely candidates for the development of human-safe actuators. In this paper, the safety characteristics of the DASA approach are qualitatively discussed. Experimental results highlighting the performance capability of the developed robot are given.

In absence of tactile and visual sensors, manipulators rely on dynamic modeling and force/torque sensors to detect collisions. Predicated upon the understanding that collision detection will be improved by removing the effects of torque sensor error and friction compensation error, we propose an approach to measure these undesired effects in external torque residual signals without resorting to remodeling of the robot. Compensation of these effects leads to the proposed velocity-based variable thresholds which are shown to detect collisions with better efficacy than uncompensated methods. Implementation of the proposed velocity-based variable thresholds on a torque sensor equipped robot validates our methodology.

In this paper, the presence of limit cycles in the behavior of antagonistically coupled Magneto-Rheological (MR) actuators is investigated. The actuator considered in this paper was developed and described in [1] and [2]. This actuator offers high torque-to-mass and torque-to-inertia ratios, for inherent safe actuation. While the antagonistic arrangement is beneficial in improving the actuator performance and eliminating backlash, it may result in limit cycles when the actuator operates in a position control loop. The occurrence of limit cycle depends on the parameters of the actuator as well as the controller. An in-depth analysis is carried out in this paper to establish a connection between the system parameters and the limit cycle occurrence. Moreover, sufficient conditions for avoiding limit cycle are derived specifically for a Proportional-Derivative (PD) controller. Simulations and experimental results validate the analysis and provide insights into the limit cycle observed in the operation of antagonistic MR actuators.

This paper presents the design and development of a novel two Degrees-Of-Freedom (DOF) safe robot manipulator. Magneto-Rheological (MR) clutches are incorporated in the design to enable antagonistic actuation at the joints. A single unidirectional motor supports bidirectional actuation of all joints. Unlike most current safe robots, high quality actuation is preserved, while the manipulator weight and effective inertia are reduced. This is achieved by relocating the driving motor to the base of the robot. Moreover, MR clutches have been shown to pose superior torque to mass, and torque to inertia characteristics over conventional servo motors, further contributing to the reduction of manipulator mass and inertia. The manipulator exhibits both high performance and intrinsic safety as a result of mechanically passive dynamics. A set of experiments is performed to validate the manipulator performance.

In this paper, adaptive compensation of the hysteresis in a Magneto-Rheological (MR) fluid based actuators and its application for sensor-less high fidelity force/torque control is investigated. The MR actuator considered in this paper was originally described in [1] and [2]. This actuator offers high torque-to-mass and torque-to-inertia ratios. Yet, as an essential component of MR actuators, the magnetic circuit of the actuator shows hysteresis between its input current/voltage and output magnetic field. The hysteresis in the magnetic circuit results in a similar relationship between the input current and the output torque of the MR actuator. The control scheme used with actuators possessing hysteresis often requires compensating for the hysteresis. To this end, we propose an adaptive control method based on feedback linearization that estimates both hysteresis and uncertain parameters of the magnetic circuit. A set of experiments is performed to validate the effectiveness of the proposed method.

In this paper, a new open-loop model for a Magneto-Rheological (MR) based actuator is presented. The model consists of two parts relating the output torque of the actuator to its internal magnetic field, and the internal magnetic field to the applied current. Each part possesses its own hysteretic behavior. The first part uses an open-loop Bouc-Wen model to relate the output torque to internal magnetic field. The second part uses a novel nonlinear adaptive observer that relates the internal magnetic field to the applied current. The model facilitates accurate control of the actuator using its input current. It also eliminates the need for force/torque sensors for providing feedback signals. The accuracy of the constructed model is validated through simulations. The overall model as well as each part of it is assessed against a widely accepted hysteresis modeling approach, known as the Preisach model and its advantages are highlighted. The second part of model is also compared to Bingham model which has been broadly employed in modeling of MR fluid dynamic. Bouc-Wen model shows higher accuracy in capturing hysteretic behavior of MR fluid in comparison to non-hysteretic Bingham model. Experimental results using the prototyped actuation mechanism further verify the accuracy of the model and demonstrate its effectiveness.

Modeling errors are one of the elements responsible for deficiencies in sensorless collision detection of robotic systems. By providing a specific formulation of manipulator equations, this paper presents a time-variant threshold for observer residues in joint space of a manipulator in order to provide more accurate collision detection ability compared to constant thresholds. The time-variant threshold considers modeling errors in both robot's parameters and its friction forces. Simulation results using real-life collision forces and experiments on the Phantom Omni device are provided to validate the proposed scheme.

This paper presents a new approach to account for distributed friction in needle insertion in soft tissue. As is well known, friction is a complex nonlinear phenomenon, and it appears that classical or static models are unable to capture some of the observations in systems subject to significant frictional effects. To characterize dynamic features when the needle is very flexible and friction plays an important role in bending mechanics or when a stop-and-start planning scenario is implemented at low insertion velocities, a distributed LuGre model can be adopted. Experimental results using an artificial phantom illustrate that the proposed method is capable of representing the main features of friction which is a major force component in needle-tissue interaction during percutaneous interventions.

Interactive robots are required to have minimal footprint on the shop floor and to be able to work in constrained areas while ensuring the safety of the humans. To this end, modeling of an unstructured environment including the humans is an indispensable part of the online control schemes deployed in such robots. In this regard, a new approach is proposed for generating an efficient model of the human body. This model takes advantage of superquadric functions to represent the human body more realistically than using primitive shapes, while offering minimal computational complexity and simplicity of further computations in comparison to the existing articulated models. This approach is also capable of incorporating various body postures and arbitrary arm configurations in the model. In addition, a new and intelligent sensory system, called floor mat, is introduced which can significantly contribute to generation of the proposed model, in a timely manner. The integration of the floor mat in a multi-sensory system for obtaining all required data for rendering the real-time 3D human model is then discussed. The use of superquadric-based human model in conjunction with the proposed sensing techniques provides an accurate, yet computationally efficient solution for safe human-robot interactions (HRI).

In this paper we present the design and experimental validation of a Magneto-Rheological (MR) clutch developed for servo control applications in human friendly robotic systems. The clutch is developed as a practical prototype for potential industrial applications in the low to mid torque range. Conventional servo motors have been shown to lack the necessary properties to deliver intrinsically safe actuation for physical interaction with humans. Several human safe actuation paradigms have been proposed, however, tend to increase mechanical complexity as well as require more sophisticated control strategies. Furthermore, many of the proposed solutions have failed to demonstrate a practical implementation that provides the necessary performance capabilities required for practical applications in automation, as well as more general servo control applications. MR clutch devices have been shown to provide favorable characteristics for such tasks, however have focused primarily on haptic systems or low torque applications. The developed prototype MR clutch is capable of transmitting up to 75 Nm, and has a control bandwidth of approximately 30 Hz.

This paper presents a new needle deflection model that is an extension of prior work in our group based on the principles of beam theory. The use of a long flexible needle in percutaneous interventions necessitates accurate modeling of the generated curved trajectory when the needle interacts with soft tissue. Finding a feasible model is important in simulators with applications in training novice clinicians or in path planners used for needle guidance. Using intra-operative force measurements at the needle base, our approach relates mechanical and geometric properties of needle-tissue interaction to the net amount of deflection and estimates the needle curvature. To this end, tissue resistance is modeled by introducing virtual springs along the needle shaft, and the impact of needle-tissue friction is considered by adding a moving distributed external force to the bending equations. Cutting force is also incorporated by finding its equivalent sub-boundary conditions. Subsequently, the closed-from solution of the partial differential equations governing the planar deflection is obtained using Green's functions. To evaluate the performance of our model, experiments were carried out on artificial phantoms.

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.

In this paper a reactive control strategy intended for human-robot interactions (HRI) is presented. A conventional reactive control scheme is reviewed first. This is followed by the introduction of a new prediction-based reactive control strategy. The new control strategy considers foreseeable dangerous events by predicting human motion using artificial neural networks, based on the previous pattern of the motion. This approach enables a robot to foresee an upcoming danger in order to take preventive actions before the danger is immanent. Experimental results for a CRS-F3 robot manipulator are presented in order to demonstrate and validate the effectiveness of this method.

For several decades now, the robotics industry has postulated the emergence of a new breed of manipulators capable of safely interacting with humans. The integration of robots into human environments has always possessed a unique set of challenges. The primary concern has always been for the safety of the human coworkers. Insuring their safety has led to the desire to design manipulators with intrinsic safety characteristics. Specifically, it is noted that modern `human-safe' manipulators are successful if they have minimized both their weight and reflected actuator inertia. The leading research accomplishing this relies on complex actuation systems. Such systems commonly suffer from degraded performance and high cost of development. Magneto- and electro-rheological fluids are a class of smart-materials that can instantaneously, and reversibly alter their rheological properties under the influence of an applied field. Devices developed with such fluids are known to possess superior torque-to-inertia characteristics over conventional servo systems. Moreover, their simple mechanical construction suggests that manipulators using such devices could be developed at a lower cost. In this paper, we will discuss the potential benefits rheological fluids can bring to the field of human friendly manipulators.

In this paper, the application of a piezoelectric stack actuator for vibration control in a large-scale robotic manipulator, called a macromanipulator, is studied. In this regard, mechanical design and mathematical modeling of the actuator are discussed. The structural flexibility of the macromanipulator includes deflection and torsional vibration modes. The vibration modes are detected using appropriate sensor attachments. Furthermore, a nominal transfer function matrix between the input signals to the actuators and the output voltages of the sensors is obtained. A closed-loop controller based on the obtained model is designed. Because of the presence of deflection and torsional vibration modes and model uncertainties resulting from manipulator motion, an robust controller is utilized. Experimental results are presented to validate the robustness and performance of the designed controller.

In this paper, the application of a piezoelectric stack actuator for vibration control in a large-scale robotic manipulator, called the macro manipulator, is studied. The structural flexibility of the system includes deflection and torsional vibration modes. The vibration modes are detected using an appropriate sensor attachment. A nominal transfer function matrix between the input signals of the actuators and the output voltages of the sensors is obtained. A closed-loop controller based on the obtained model is designed. Because of the presence of different vibrational modes and model uncertainties resulting from manipulator motion as well as its varying payloads, an Hinfinrobust controller is utilized and experimental results are presented

In this paper, the application of high control authority piezoelectric stack actuators, in short piezostack actuators, for active vibration control of long-reach robotic manipulators is studied. The idea is to include piezostack actuators in the base structure in order to strengthen its stiffness characteristics. A mechanism is designed for converting the force produced by a piezostack actuator to a bending moment. A flexible link actuated with a piezostack actuator is built and mathematically modeled. The solution of the governing partial differential equation with non-homogenous boundary conditions is obtained. A comparison between experimental frequency response of the system and its model is given. A control law using the Popov criterion is obtained and experimental results for closed-loop system are given.

In this paper the application of high control authority piezostack actuators (PSA) for active vibration control in flexible manipulators is studied. The idea is to incorporate the piezostack actuators into the system in order to strengthen its stiffness characteristics. In this regard a cantilever beam actuated with piezostack actuators is considered. A mechanism for converting the blocking force of the PSA to a bending moment is studied and a model for the whole system consisting of a flexible beam and B A is obtained. The simulation results show that the suggested method may open new possibilities in active vibration control of large flexible manipulator.

In this paper, friction compensation in robotic manipulators is studied. An observer based model of the friction force is utilized for the friction compensation algorithm. In order to evaluate the efficiency of this method two different manipulators with different friction characteristics are examined. A 2-DOF manipulator used for high-speed, micro-meter precision manipulation and a 4-DOF macro manipulator used for long reach positioning task are examined. These manipulators are characterized, according to compensation task classifications (Armstrong, B. et al., 1994), as high-reversal-velocity and low-reversal-velocity tracking tasks, respectively. In each case a steady-state model of friction is experimentally obtained. This model is further utilized in dynamic equations of the friction force during manipulation. It is shown that despite the different nature of the two manipulators the same method can effectively improve the speed and performance of the manipulation in both cases.

This paper discusses the selection process for piezoelectric transducers (PZT) used as actuator elements for suppressing vibrations in a flexible beam system. The effects of changing physical parameters such as the relative thickness of the piezoelectric ceramic with respect to the beam, the optimum location of the PZT actuator, and the length of the PZT are studied based on the singular value decomposition of the controllability Grammian of the resulting system. A model for a clamped-mass cantilevered beam is developed and its frequency response is compared with that obtained experimentally. Simulation results are given to illustrate how this method can be used to determine physical properties and location of the PZT actuator. Further experimental studies are currently being performed.