System identification is a key discipline within the field of automation that deals with inferring mathematical models of dynamic systems based on input-output measurements. Conventional identification methods require extensive data generation and are thus not suitable for real-time applications. In this paper, a novel real-time approach for the parametric identification of linear systems using Deep Learning (DL) and the Modified Relay Feedback Test (MRFT) is proposed. The proposed approach requires only a single steady-state cycle of MRFT, and guarantees stability and performance in the identification and control phases. The MRFT output is passed to a trained DL model that identifies the underlying process parameters in milliseconds. A novel modification to the Softmax function is derived to better conform the DL model for the process identification task. Quadrotor Unmanned Aerial Vehicle (UAV) attitude and altitude dynamics were used in simulation and experimentation to verify the presented approach. Results show the effectiveness and real-time capabilities of the proposed approach, which outperforms the conventional Prediction Error Method in terms of accuracy, robustness to biases, computational efficiency and data requirements.

The global increase in the number of stroke patients and limited accessibility to rehabilitation has promoted an increase in the design and development of mobile exoskeletons. Robot-assisted mobile rehabilitation is rapidly emerging as a viable tool as it could provide intensive repetitive movement training and timely standardized delivery of therapy as compared to conventional manual therapy. However, the majority of existing lower limb exoskeletons continue to be heavy and induce unnecessary inertia and inertial vibration on the limb. Cable-driven exoskeletons can overcome these issues with the provision of remote actuation. However, the number of cables and routing can be selected in various ways posing a challenge to designers regarding the optimal design configuration. In this work, a simulation-based generalized framework for modelling and assessment of cable-driven mobile exoskeleton is proposed. The framework can be implemented to identify a ‘suitable’ configuration from several potential ones or to identify the optimal routing parameters for a given configuration. For a proof of concept, four conceptual configurations of cable-driven exoskeletons (one with a spring) were developed in a manner where both positive and negative moments could be generated for each joint (antagonistic configuration). The models were analyzed using the proposed framework and a decision metric table has been developed based on the models’ performance and requirements. The weight of the metrics can be adjusted depending on the preferences and specified constraints. The maximum score is assigned to the configuration with minimum requirement or error, maximum performance, and vice versa. The metric table indicated that the 4-cable configuration is a promising design option for a lower limb rehabilitation exoskeleton based on tracking performance, model requirements, and component forces exerted on the limb.

In this paper we present the design and characterization of a novel Passive Variable Stiffness Joint (pVSJ). pVSJ is the proof of concept of a passive revolute joint with controllable variable stiffness. The current design is intended to be a bench-test for future development towards applications in haptic teleoperation purposed exoskeletons. The main feature of the pVSJ is its capability of varying the stiffness with infinite range based on a simple mechanical system. Moreover, the joint can rotate freely at the zero stiffness case without any limitation. The stiffness varying mechanism consists of two torsional springs, mounted with an offset from the pVSJ rotation center and coupled with the joint shaft by an idle roller. The position of the roller between the pVSJ rotation center and the spring's center is controlled by a linear sliding actuator fitted on the chassis of the joint. The variation of the output stiffness is obtained by changing the distance from the roller-springs contact point to the joint rotation center (effective arm). If this effective arm is null, the stiffness of the joint will be zero. The stiffness increases to reach high stiffness values when the effective arm approaches its maximum value, bringing the roller close to the torsional springs' center. The experimental results matched with the physical-based modeling of the pVSJ in terms of stiffness variation curve, stiffness dependency upon the springs' elasticity, joint deflection and the spring's deflection

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In this paper, the modeling, design, and characterization of the passive discrete variable stiffness joint (pDVSJ-II) are presented. The pDVSJ-II is an extended proof of concept of a passive revolute joint with discretely controlled variable stiffness. The key motivation behind this design is the need for instantaneous switching between stiffness levels when applied for remote exploration applications where stiffness mapping is required, in addition for the need of low-energy consumption. The novelty of this work lies in the topology used to alter the stiffness of the variable stiffness joint. Altering the stiffness is achieved by selecting the effective length of an elastic cord with hook's springs. This is realized through the novel design of the cord grounding unit (CGU), which is responsible for creating a new grounding point, thus changing the effective length and the involved springs. The main features of CGU are the fast response and the low-energy consumption. Two different levels of stiffness (low, high) can be discretely selected besides the zero stiffness. The proposed physical-based model matched the experimental results of the pDVSJ-II in terms of discrete stiffness variation curves, and the stiffness dependency on the behavior of the springs. Two psychophysiological tests were conducted to validate the capabilities to simulate different levels of stiffness on human user and the results showed high relative accuracy. Furthermore, a qualitative experiment in a teleoperation scenario is presented as a case study to demonstrate the effectiveness of the proposed haptic interface.