Model-Based Mid-Level Regulation for Assist-As-Needed Hierarchical Control of Wearable Robots: A Computational Study of Human-Robot Adaptation

The closed-loop human–robot system requires developing an effective robotic controller that considers models of both the human and the robot, as well as human adaptation to the robot. This paper develops a mid-level controller providing assist-as-needed (AAN) policies in a hierarchical control setting using two novel methods: model-based and fuzzy logic rule. The goal of AAN is to provide the required extra torque because of the robot’s dynamics and external load compared to the human limb free movement. The human–robot adaptation is simulated using a nonlinear model predictive controller (NMPC) as the human central nervous system (CNS) for three conditions of initial (the initial session of wearing the robot, without any previous experience), short-term (the entire first session, e.g., 45 min), and long-term experiences. The results showed that the two methods (model-based and fuzzy logic) outperform the traditional proportional method in providing AAN by considering distinctive human and robot models. Additionally, the CNS actuator model has difficulty in the initial experience and activates both antagonist and agonist muscles to reduce movement oscillations. In the long-term experience, the simulation shows no oscillation when the CNS NMPC learns the robot model and modifies its weights to simulate realistic human behavior. We found that the desired strength of the robot should be increased gradually to ignore unexpected human–robot interactions (e.g., robot vibration, human spasticity). The proposed mid-level controllers can be used for wearable assistive devices, exoskeletons, and rehabilitation robots.

Dynamic Analysis of a Spherical Parallel Robot Used for Brachial Monoparesis Rehabilitation

This paper presents studies on the dynamic analysis of the ASPIRE robot, which was designed for the medical recovery of brachial monoparesis. It starts from the virtual model of the existing version of the ASPIRE robot, which is analysed kinematically and dynamically by numerical simulations using the MSC.ADAMS software. For this purpose, this paper presents theoretical aspects regarding the kinematics and dynamics of the markers attached to the flexible bodies built in a specifically developed MSC.ADAMS model. Three simulation hypotheses are considered: (a) rigid kinematic elements without friction in couplings, (b) rigid kinematic elements with friction in couplings, and (c) kinematic elements as deformable solids with friction in couplings. Experimental results obtained by using the physical prototype of ASPIRE are presented. Results such as the connecting forces in the kinematic joints and the torques necessary to operate the ASPIRE robot modules have been obtained by dynamic simulation in MSC.ADAMS and compared with those determined experimentally. The comparison shows that the allure of the variation curve of the moment obtained by simulation is similar to that obtained experimentally. The difference between the maximum experimental value and that obtained by simulation is less than 1%. A finite element analysis (FEA) of the structurally optimized flexion/extension robot module is performed. The results demonstrate the operational safety of the ASPIRE robot, which is structurally capable of supporting the stresses to which it is subjected.

Control of the Sit-To-Stand Transfer of a Biped Robotic Device for Postural Rehabilitation

This paper deals with the control of the sit-to-stand transfer of a biped robotic device (either an autonomous biped robot or a haptic assistive exoskeleton for postural rehabilitation). The control has been synthesized, instead of considering the physiology, analyzing the basic laws of dynamics. The transfer of a human from sitting on a chair to an erect posture is an interesting case study, because it treats biped balance in a two-phase dynamic setting, with an external force disturbance (the chair–pelvis contact) affecting the center of pressure under the feet. At the beginning, a body is sitting, with a fixed pelvis moving with the hips going toward the supporting feet and, contemporaneously, releasing the load from the chair with ankles and knee torques. Then, after lift-off, it reaches and maintains an erect posture. The paper objectives are threefold: identifying the major dynamical determinants of the exercise; sythesizing an automatic control for an autonomous device; proposing an innovative approach for the rehabilitation process with an exoskeleton. For this last objective, the paper extends the idea of the authors of a haptic exoskeleton for rehabilitation. It is driven to control the joints by electromiographical signals from the patient. The two spaces, cartesian (world) and joint, where, respectively, the automatic control and the patient operate, are considered and a technique to blend the two actions is proposed. The exoskeleton is programed to perform the exercise autonomously. Then, during the evolution of the phases of rehabilitation, we postulated to seamlessly move the control from one space (purely autonomous) to another (completely driven by the patient), choosing and keeping the postural tasks and joints (heaps, knees, or ankles) on which to apply each one of the two actions without interaction.

Estimation and Closed-Loop Control of COG/ZMP in Biped Devices Blending CoP Measures and Kinematic Information

The zero moment point ( Z M P ) and the linearized inverted pendulum model linking the Z M P to the center of gravity ( C O G ) have an important role in the control of the postural equilibrium (balance) of biped robots and lower-limb exoskeletons. A solution for balance real time control, closing the loop from the joint actual values of the C O G and Z M P , has been proposed by Choi. However, this approach cannot be practically implemented: While the Z M P actual value is available from the center of pressure ( C o P ) measured under the feet soles, the C O G is not measurable, but it can only be indirectly assessed from the joint-angle measures, the knowledge of the kinematics, and the usually poorly known weight distribution of the links of the chain. Finally, the possible presence of unknown external disturbance forces and the nonlinear, complex nature of the kinematics perturb the simple relationship between the Z M P and C O G in the linearized model. The aim of this paper is to offer, starting from Choi’s model, a practical implementation of closed-loop balance control fusing C o P and joint-angle measures, eliminating possible inconsistencies. In order to achieve this result, we introduce a model of the linearized inverted pendulum for an extended estimation, not only of C O G and Z M P , but also of external disturbances. This model is then used, instead of Choi’s equations, for estimation and balance control, using H ∞ theory. As the C O G information is recovered from the joint-angle measures, the identification of a statistically equivalent serial chain ( S E S C ) linking the C O G to the joint angles is also discussed.

Proportional myoelectric and compensating control of a cable-conduit mechanism-driven upper limb exoskeleton

Recent studies have indicated that human motion recognition based on surface electromyography (sEMG) is a reliable and natural method for achieving motion intention. However, achieving accurate estimates of intended motion using a low computational cost is the main challenge in this scenario. In this study, a proportional myoelectric and compensating control method for estimating and assisting human motion intention with a cable-conduit mechanism-driven upper limb exoskeleton was proposed. The integral signal of sEMG and its time-delayed signals were applied as a new feature vector to represent the role of sEMG, which ensured the accuracy and real-time performance of motion estimation. An integrated circuit was used to reduce time of feature extraction. A feed-forward compensator was designed to compensate for the effect of the hysteresis problem in the exoskeleton, which is inevitable when the cable-conduit mechanism was applied to reduce the exoskeleton weight. The model-free control method based on PID method and least squares support vector machine were applied to avoid calculating the complex biomechanical model of human upper limb and the dynamic model of exoskeleton. Experimental results validated the proposed method. The average values of the root-mean-square difference (RMSD) for motion estimation were 0.0579 ± 0.0085 [motion with constant pace (CP)] and 0.0845 ± 0.0137 [motion with variable pace (VP)]. The Bland-Altman analysis results showed that the estimated angle of the proposed method was consistent with the actual angle. The performance of the control method was good, and the accuracies were 98.5608% ± 0.4485% (motion with CP) and 96.6119% ± 0.6628% (motion with VP).

Extending the Application of an Assistant Personal Robot as a Walk-Helper Tool

This paper presents the application of a mobile robot designed as an Assistant Personal Robot (APR) as a walk-helper tool. The hypothesis is that the height and weight of this mobile robot can be used also to provide a dynamic physical support and guidance to people while they walk. This functionality is presented as a soft walking aid at home but not as a substitute of an assistive cane or a walker device, which may withstand higher weights and provide better stability during a walking. The APR operates as a walk-helper tool by providing user interaction using the original arms of the mobile robot and by using the onboard sensors of the mobile robot in order to avoid obstacles and guide the walking through free areas. The results of the experiments conducted with the walk-helper have showed the automatic generation of smooth walking trajectories and a reduction in the number of manual trajectory corrections required to complete a walking displacement.