Arash Ajoudani

Tele-impedance: Teleoperation with impedance regulation using a body-machine interface

This work presents the concept of tele-impedance as a method for remotely controlling a robotic arm in interaction with uncertain environments. As an alternative to bilateral force-reflecting teleoperation control, in tele-impedance a compound reference command is sent to the slave robot including both the desired motion trajectory and impedance profile, which are then realized by the remote controller without explicit feedback to the operator. We derive the reference command from a novel body–machine interface (BMI) applied to the master operator’s arm, using only non-intrusive position and electromyography (EMG) measurements, and excluding any feedback from the remote site except for looking at the task. The proposed BMI exploits a novel algorithm to decouple the estimates of force and stiffness of the human arm while performing the task. The endpoint (wrist) position of the human arm is monitored by an optical tracking system and used for the closed-loop position control of the robot’s end-effector. The concept is demonstrated in two experiments, namely a peg-in-the-hole and a ball-catching task, which illustrate complementary aspects of the method. The performance of tele-impedance control is assessed by comparing the results obtained with the slave arm under either constantly low or high stiffness.

Proceedings of the first workshop on peripheral machine interfaces: Going beyond traditional surface electromyography

One of the hottest topics in rehabilitation robotics is that of proper control of prosthetic devices. Despite decades of research, the state of the art is dramatically behind the expectations. To shed light on this issue, in June, 2013 the first international workshop on Present and future of non-invasive peripheral nervous system (PNS)–Machine Interfaces (MI; PMI) was convened, hosted by the International Conference on Rehabilitation Robotics. The keyword PMI has been selected to denote human–machine interfaces targeted at the limb-deficient, mainly upper-limb amputees, dealing with signals gathered from the PNS in a non-invasive way, that is, from the surface of the residuum. The workshop was intended to provide an overview of the state of the art and future perspectives of such interfaces; this paper represents is a collection of opinions expressed by each and every researcher/group involved in it.

A Neuro-Sliding-Mode Control With Adaptive Modeling of Uncertainty for Control of Movement in Paralyzed Limbs Using Functional Electrical Stimulation

During the past several years, several strategies have been proposed for control of joint movement in paraplegic subjects using functional electrical stimulation (FES), but developing a control strategy that provides satisfactory tracking performance, to be robust against time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, muscle fatigue, and external disturbances, and to be easy to apply without any re-identification of plant dynamics during different experiment sessions is still an open problem. In this paper, we propose a novel control methodology that is based on synergistic combination of neural networks with sliding-mode control (SMC) for controlling FES. The main advantage of SMC derives from the property of robustness to system uncertainties and external disturbances. However, the main drawback of the standard sliding modes is mostly related to the so-called chattering caused by the high-frequency control switching. To eliminate the chattering, we couple two neural networks with online learning without any offline training into the SMC. A recurrent neural network is used to model the uncertainties and provide an auxiliary equivalent control to keep the uncertainties to low values, and consequently, to use an SMC with lower switching gain. The second neural network consists of a single neuron and is used as an auxiliary controller. The control law will be switched from the SMC to neural control, when the state trajectory of system enters in some boundary layer around the sliding surface. Extensive simulations and experiments on healthy and paraplegic subjects are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed neuroadaptive SMC. The results show that the neuro-SMC provides accurate tracking control with fast convergence for different reference trajectories and could generate control signals to compensate the muscle fatigue and reject the external disturbance.

Exploring Teleimpedance and Tactile Feedback for Intuitive Control of the Pisa/IIT SoftHand

This paper proposes a teleimpedance controller with tactile feedback for more intuitive control of the Pisa/IIT SoftHand. With the aim to realize a robust, efficient and low-cost hand prosthesis design, the SoftHand is developed based on the motor control principle of synergies, through which the immense complexity of the hand is simplified into distinct motor patterns. Due to the built-in flexibility of the hand joints, as the SoftHand grasps, it follows a synergistic path while allowing grasping of objects of various shapes using only a single motor. The DC motor of the hand incorporates a novel teleimpedance control in which the users postural and stiffness synergy references are tracked in real-time. In addition, for intuitive control of the hand, two tactile interfaces are developed. The first interface (mechanotactile) exploits a disturbance observer which estimates the interaction forces in contact with the grasped object. Estimated interaction forces are then converted and applied to the upper arm of the user via a custom made pressure cuff. The second interface employs vibrotactile feedback based on surface irregularities and acceleration signals and is used to provide the user with information about the surface properties of the object as well as detection of object slippage while grasping. Grasp robustness and intuitiveness of hand control were evaluated in two sets of experiments. Results suggest that incorporating the aforementioned haptic feedback strategies, together with user-driven compliance of the hand, facilitate execution of safe and stable grasps, while suggesting that a low-cost, robust hand employing hardware-based synergies might be a good alternative to traditional myoelectric prostheses.

WALK‐MAN: A High‐Performance Humanoid Platform for Realistic Environments

In this work, we present WALK-MAN, a humanoid platform that has been developed to operate in realistic unstructured environment, and demonstrate new skills including powerful manipulation, robust balanced locomotion, high-strength capabilities, and physical sturdiness. To enable these capabilities, WALK-MAN design and actuation are based on the most recent advancements of series elastic actuator drives with unique performance features that differentiate the robot from previous state-of-the-art compliant actuated robots. Physical interaction performance is benefited by both active and passive adaptation, thanks to WALK-MAN actuation that combines customized high-performance modules with tuned torque/velocity curves and transmission elasticity for high-speed adaptation response and motion reactions to disturbances. WALK-MAN design also includes innovative design optimization features that consider the selection of kinematic structure and the placement of the actuators with the body structure to maximize the robot performance. Physical robustness is ensured with the integration of elastic transmission, proprioceptive sensing, and control. The WALK-MAN hardware was designed and built in 11 months, and the prototype of the robot was ready four months before DARPA Robotics Challenge (DRC) Finals. The motion generation of WALK-MAN is based on the unified motion-generation framework of whole-body locomotion and manipulation (termed loco-manipulation). WALK-MAN is able to execute simple loco-manipulation behaviors synthesized by combining different primitives defining the behavior of the center of gravity, the motion of the hands, legs, and head, the body attitude and posture, and the constrained body parts such as joint limits and contacts. The motion-generation framework including the specific motion modules and software architecture is discussed in detail. A rich perception system allows the robot to perceive and generate 3D representations of the environment as well as detect contacts and sense physical interaction force and moments. The operator station that pilots use to control the robot provides a rich pilot interface with different control modes and a number of teleoperated or semiautonomous command features. The capability of the robot and the performance of the individual motion control and perception modules were validated during the DRC in which the robot was able to demonstrate exceptional physical resilience and execute some of the tasks during the competition.

Tele-Impedance based stiffness and motion augmentation for a knee exoskeleton device

In this paper, a knee exoskeleton device and its Tele-Impedance based assistive control scheme is presented. The exoskeleton device is an inherently compliant actuated system that was implemented based on the series elastic actuation (SEA) to provide improved and intrinsically soft interaction behaviour. Details of the exoskeleton design are presented. A detailed musculoskeletal model was developed and experimentally identified in order to map electromyographic signals to the antagonistic muscle torques, acting on the human knee joint. The estimated muscle torques are used in order to determine the users intent and joint stiffness trend. These reference signals are exploited by a novel Tele-Impedance controller which is applied to a knee exoskeleton device to provide assistance and stiffness augmentation to the users knee joint. Experimental trials of a standing-up motion task were carried out for evaluation of the proposed control strategy. The results indicate that the proposed knee exoskeleton device and control scheme can effectively generate assistive actions that are intrinsically and naturally controlled by the user muscle activity.

Tele-impedance: Towards transferring human impedance regulation skills to robots

This work presents the novel concept of Tele-Impedance as a method for controlling/teleoperating a robotic arm while performing tasks which require significant dynamics variation. As an alternative method to bilateral force-reflecting teleoperation control approach, which uses a position/velocity command combined with force feedback from the robot side, Tele-Impedance enriches the command sent to the slave robot by combining the position reference with a stiffness (or full impedance) reference estimated from the arm of the human operator. We propose a new method to estimate the stiffness of the human arm based on the agonist-antagonist muscular co activations. The concept of the Tele-Impedance is demonstrated using the KUKA light weight robotic arm as the slave manipulator in a ball reception experiment. The performance of Tele-Impedance control method is assessed by comparing the results obtained while receiving the ball, with the slave arm under i) constant low stiffness, ii) constant high stiffness or iii) under Tele-Impedance control. Performance indexes are defined and used for the comparative study of the ball reception performances under the different endpoint elastic profiles. The experimental results demonstrate the effectiveness of the task-related Tele-Impedance control method and highlight its potential use to execute tasks which require significant dynamics variation.

Tele-impedance based assistive control for a compliant knee exoskeleton

This paper presents a tele-impedance based assistive control scheme for a knee exoskeleton device. The proposed controller captures the users intent to generate task-related assistive torques by means of the exoskeleton in different phases of the subjects normal activity. To do so, a detailed musculoskeletal model of the human knee is developed and experimentally calibrated to best match the users kinematic and dynamic behavior. Three dominant antagonistic muscle pairs are used in our model, in which electromyography (EMG) signals are acquired, processed and used for the estimation of the knee joint torque, trajectory and the stiffness trend, in real time. The estimated stiffness trend is then scaled and mapped to a task-related stiffness interval to agree with the desired degree of assistance. The desired stiffness and equilibrium trajectories are then tracked by the exoskeletons impedance controller. As a consequence, while minimum muscular activity corresponds to low stiffness, i.e.?highly transparent motion, higher co-contractions result in a stiffer joint and a greater level of assistance. To evaluate the robustness of the proposed technique, a study of the dynamics of the human-exoskeleton system is conducted, while the stability in the steady state and transient condition is investigated. In addition, experimental results of standing-up and sitting-down tasks are demonstrated to further investigate the capabilities of the controller. The results indicate that the compliant knee exoskeleton, incorporating the proposed tele-impedance controller, can effectively generate assistive actions that are volitionally and intuitively controlled by the users muscle activity. We propose a tele-impedance based assistive control for a knee exoskeleton.An EMG-driven biomechanical model estimates the net torque and joint stiffness trend index.The outputs of the model are used to derive the trajectory and stiffness of the exoskeletons impedance controller.The exoskeleton can generate assistive actions that are volitionally controlled by the users muscle activity.

Tele-Impedance: Preliminary results on measuring and replicating human arm impedance in tele operated robots

This work introduces the concept of Tele-Impedance as a method for controlling/teleoperating a robotic arm in contact with the environment. Opposite to bilateral force-reflecting teleoperation control approach, which uses a position/velocity command combined with force feedback from the robot side, Tele-Impedance enriches the command sent to the slave robot by combining the position reference with a stiffness (or full impedance) reference. The desired stiffness profile is directly estimated from the arm of the human operating the remote robotic arm. We preliminarily investigate the effectiveness of this method while teleoperating a slave robotic arm to execute simple tasks. The KUKA light weight robotic arm is used as the slave manipulator. The endpoint (wrist) position of the human arm is monitored by an optical tracking system while the stiffness of the human arm is estimated from the electromyography (EMGs) signal measurements of four flexor-extensor muscle pairs, in realtime. The performance of Tele-Impedance control method is assessed by comparing the results obtained while executing a peg-in-hole task, with the slave arm under i) constant low stiffness, ii) constant high stiffness or iii) under Tele-Impedance control. The experimental results demonstrate the effectiveness of the Tele-Impedance control method and highlight its potential use to safely execute tasks with uncertain environment constraints which may result in large deviations from the commanded position trajectories.

A manipulation framework for compliant humanoid COMAN: Application to a valve turning task

With the purpose of achieving a desired interaction performance for our compliant humanoid robot (COMAN), in this paper we propose a semi-autonomous control framework and evaluate it experimentally in a valve turning setup. The control structure consists of various modules and interfaces to identify the valve, locate the robot in front of it and perform the manipulation. The manipulation module implements four motion primitives (Reach, Grasp, Rotate and Disengage) and realizes the corresponding desired impedance profile for each phase to accomplish the task. In this direction, to establish a stable and compliant contact between the valve and the robot hands, while being able to generate the sufficient rotational torques depending on the valves friction, Rotate incorporates a novel dual-arm impedance control technique to plan and realize a task-appropriate impedance profile. Results of the implementation of the proposed control framework are firstly evaluated in simulation studies using Gazebo. Subsequent experimental results highlight the efficiency of the proposed impedance planning and control in generation of the required interaction forces to accomplish the task.