Novel Design and Implementation of a Knee Exoskeleton for Gait Rehabilitation with Impedance Control Strategy

This paper presents a novel cable-driven robotic joint for a gait exoskeleton robot. We discussed in detail a lightweight, low inertia, and highly back-drivable, 1-DOF tension amplification mechanism based on a pulley system and block-and-tackle technique. The exoskeleton is controlled using an impedance controller under the active-assistive and resistive approaches. Four experiments were conducted to evaluate the proposed exoskeleton’s safety and controller performance: mechanical transparency analysis, active-assistive trajectory tracking, resistance of trajectory tracking, and gait rehabilitation. The exoskeleton demonstrated high transparency with the root mean square (RMS) torque of 0.457 Nm under no-load condition, suggesting that the mechanism is highly back-drivable, has a low moment of inertia, and is mechanically safe to operate. The active-assistive trajectory tracking experiment indicated that the output torque was generated under assist-as-needed approach, as the average robotic-assistance torque was lowered by more than 73% when the user provided assistance force to complete the task on their own.  Additionally, the resistance experiment revealed the feasibility of employing the exoskeleton to strengthen muscles with adjustable resistive torque from 0.94 Nm and 2.25 Nm. Finally, the result of gait rehabilitation experiment demonstrated that the robot was able to provide adequate torque to assist users in completing their gait cycle without causing any negative effects during or after the experiment

Design and Characterization of a Novel High-Power Series Elastic Actuator for a Lower Limb Robotic Orthosis

A safe interaction is crucial in wearable robotics in general, while in assistive and rehabilitation applications, robots may also be required to minimally perturb physiological movements, ideally acting as perfectly transparent machines. The actuation system plays a central role because the expected performance, in terms of torque, speed and control bandwidth, must not be achieved at the expense of lightness and compactness. Actuators embedding compliant elements, such as series elastic actuators, can be designed to meet the above-mentioned requirements in terms of high energy storing capacity and stability of torque control. A number of series elastic actuators have been proposed over the past 20 years in order to accommodate the needs arising from specific applications. This paper presents a novel series elastic actuator intended for the actuation system of a lower limb wearable robot, recently developed in our lab. The actuator is able to deliver 300 W and has a novel architecture making its centre of mass not co-located with its axis of rotation, for an easier integration into the robotic structure. A custom-made torsion spring with a stiffness of 272.25 N·m·rad– 1 is directly connected to the load. The delivered torque is calculated from the measurement of the spring deflection, through two absolute encoders. Testing on torque measurement accuracy and torque/stiffness control are reported

Design, Development and Scaling Analysis of a Variable Stiffness Magnetic Torsion Spring

In this paper we report on the design, modeling, experimental testing and scaling analysis of a novel MAgnetic Variable stiffnEess spRIng-Clutch (MAVERIC) device, which may be used as the elastic element of Variable Stiffness Actuators (VSAs). The device, comprising two co-axial diametrically magnetized hollow cylinders, has two degrees of freedom: a rotation of the two cylinders around the common axis and a relative translation along the same axis. For small rotations, the torque arising from the magnetic interaction of the two cylinders is almost linearly proportional to their relative rotation, as in mechanical torsion springs. In addition, the stiffness of the equivalent spring can be varied continuously from a maximum value down to exactly zero by changing the axial overlap of the two cylinders. In this way the proposed device can be used both as a clutch (i.e., perfectly compliant element) and as a variable stiffness torsion spring. A prototype, designed after magnetostatic FEM simulations, has been built and experimentally characterized. The developed MAVERIC has an experimentally determined maximum transmissible torque of 109.81mNm, while the calculated maximum stiffness is 110.2mNmrad−1. The amplitude of the torque-angle characteristic can be tuned linearly with a sensitivity of 12.63mNmmm−1 rad−1. Further simulations have been computed parameterizing the geometry and the number of pole pairs of the magnets. The maximum torque density reached for one pole pair is 47.21 · 103 Nm m−3, whereas for a fixed geometry similar to that of the developed prototype, the maximum torque is reached for seven pole pairs. Overall, compared to mechanical springs, MAVERIC has no fatigue or overloading issues. Compared to other magnetic couplers, torsion stiffness can be varied continuously from a maximum value down to exactly zero, when the device acts as a disengaged clutch, disconnecting the load from the actuator

A Sliding Mode Force and Position Controller Synthesis for Series Elastic Actuators

This paper deals with the robust force and position control problems of Series Elastic Actuators. It is shown that a Series Elastic Actuator's force control problem can be described by a second-order dynamic model which suffers from only matched disturbances. However, the position control dynamics of a Series Elastic Actuator is of fourth-order and includes matched and mismatched disturbances. In other words, a Series Elastic Actuator's position control is more complicated than its force control, particularly when disturbances are considered. A novel robust motion controller is proposed for Series Elastic Actuators by using Disturbance Observer and Sliding Mode Control. When the proposed robust motion controller is implemented, a Series Elastic Actuator can precisely track desired trajectories and safely contact with an unknown and dynamic environment. The proposed motion controller does not require precise dynamic models of the actuator and environment. Therefore, it can be applied to many different advanced robotic systems such as compliant humanoids and exoskeletons. The validity of the motion controller is experimentally verified.Comment: Accepted by Robotica in 201

Performance and manufacturing considerations for series elastic actuators

Robots are becoming an integral part of our lives. We are already physically connected with them through many robotic applications such as exoskeletons in military, orthosis devices in health care, collaborative robots in industry, etc. While the integration of robots improves the quality of human life, it still poses a safety concern during the physical human-robot interaction. Series Elastic Actuators (SEAs) play an important role in improving the safety of human-robot interaction and collaboration. Considering the fast expansion of robotic applications in our lives and the safety benefits of SEAs, it is conceivable that SEAs are going to play an important role in robotic applications in every aspect of human life. This dissertation focuses on reducing the cost, simplifying the use and improving the performance of SEAs. The first research focus in this dissertation is to reduce the cost of SEAs. Robots are successful in reducing production and service costs when used but the capital cost of robot installations are very high. As robotics research shifts to safe robotic applications, reducing the cost of SEAs will greatly help to deploy this technology in more robotic applications and to increase their accessibility to a broader range of researchers and educators. With this motivation, I present a case study on reducing the cost of a SEA while maintaining high force and position control performance and industrial grade service life. The second research focus in this dissertation is to simplify the laborious gain selection process of the cascaded controllers of SEAs. In order to simplify the gain selection process of the impedance controllers of SEAs, an optimal feedback gain selection methodology was developed. Using this method, the feedback gains of the cascaded PD-type impedance controllers of SEAs can easily be calibrated. The developed method allows the users to find the highest feedback gains for a desired phase-margin. Beyond the low-cost realization and simple controller tuning of SEAs, performance improvements on SEAs are possible utilizing the series elasticity in these actuators. As the third research focus in this dissertation, a sequential convex optimization-based motion planning technique is developed in order to improve the joint velocity capabilities of SEAs with nonlinearities. By using this method, higher joint velocities, that are not achievable with the rigid counterparts of SEAs can be achievedMechanical Engineerin

Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human-robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge technologies (sensors and actuators) suitable for pHRC operations and the intelligent assist devices employed in pHRC. Sensors being among the essential components to establish communication between a human and a robotic system are surveyed. The sensor supplies the signal needed to drive the robotic actuators. The survey reveals that the design of new generation collaborative robots and other intelligent robotic systems has paved the way for sophisticated learning techniques and control algorithms to be deployed in pHRC. Furthermore, it revealed the relevant components needed to be considered for effective pHRC to be accomplished. Finally, a discussion of the major advances is made, some research directions, and future challenges are presented

Learning to Assist Different Wearers in Multitasks: Efficient and Individualized Human-In-the-Loop Adaption Framework for Exoskeleton Robots

One of the typical purposes of using lower-limb exoskeleton robots is to provide assistance to the wearer by supporting their weight and augmenting their physical capabilities according to a given task and human motion intentions. The generalizability of robots across different wearers in multiple tasks is important to ensure that the robot can provide correct and effective assistance in actual implementation. However, most lower-limb exoskeleton robots exhibit only limited generalizability. Therefore, this paper proposes a human-in-the-loop learning and adaptation framework for exoskeleton robots to improve their performance in various tasks and for different wearers. To suit different wearers, an individualized walking trajectory is generated online using dynamic movement primitives and Bayes optimization. To accommodate various tasks, a task translator is constructed using a neural network to generalize a trajectory to more complex scenarios. These generalization techniques are integrated into a unified variable impedance model, which regulates the exoskeleton to provide assistance while ensuring safety. In addition, an anomaly detection network is developed to quantitatively evaluate the wearer's comfort, which is considered in the trajectory learning procedure and contributes to the relaxation of conflicts in impedance control. The proposed framework is easy to implement, because it requires proprioceptive sensors only to perform and deploy data-efficient learning schemes. This makes the exoskeleton practical for deployment in complex scenarios, accommodating different walking patterns, habits, tasks, and conflicts. Experiments and comparative studies on a lower-limb exoskeleton robot are performed to demonstrate the effectiveness of the proposed framework.Comment: 16 pages journal articl