Limited Add-On Effects of Unilateral and Bilateral Transcranial Direct Current Stimulation on Visuo-Motor Grip Force Tracking Task Training Outcome in Chronic Stroke. A Randomized Controlled Trial

Background: This randomized controlled trial investigated if uni- and bihemispheric transcranial direct current stimulation (tDCS) of the motor cortex can enhance the effects of visuo-motor grip force tracking task training and transfer to clinical assessments of upper extremity motor function.Methods: In a randomized, double-blind, sham-controlled trial, 40 chronic stroke patients underwent 5 days of visuo-motor grip force tracking task training of the paretic hand with either unilateral or bilateral (N = 15/group) or placebo tDCS (N = 10). Immediate and long-term (3 months) effects on training outcome and motor recovery (Upper Extremity Fugl-Meyer, UE-FM, Wolf Motor Function Test, and WMFT) were investigated.Results: Trained task performance significantly improved independently of tDCS in a curvilinear fashion. In the anodal stimulation group UE-FM scores were higher than in the sham group at day 5 (adjusted mean difference: 2.6, 95%CI: 0.6–4.5, p = 0.010) and at 3 months follow up (adjusted mean difference: 2.8, 95%CI: 0.8–4.7, p = 0.006). Neither training alone, nor the combination of training and tDCS improved WMFT performance.Conclusions: Visuo-motor grip force tracking task training can facilitate recovery of upper extremity function. Only minimal add-on effects of anodal but not dual tDCS were observed.Clinical Trial Registration:https://clinicaltrials.gov/ct2/results?recrs=&cond=&term=NCT01969097&cntry=&state=&city=&dist=, identifier: NCT01969097, retrospectively registered on 25/10/2013.

Critic-observer-based decentralized force/position approximate optimal control for modular and reconfigurable manipulators with uncertain environmental constraints

A critic-observer decentralized force/position approximate optimal control method is presented to address the joint trajectory and contacted force tracking problem of modular and reconfigurable manipulators (MRMs) with uncertain environmental constraints. The dynamic model of the MRM systems is formulated as an integration of joint subsystems via extensive state observer (ESO) associated with the effect of interconnected dynamic coupling (IDC). A radial basis function neural network (RBF-NN) is developed to deal with the IDC effects among the independent joint subsystems. Based on adaptive dynamic programming (ADP) approach and policy iteration (PI) algorithm, the Hamilton–Jacobi–Bellman (HJB) equation is approximately solved by establishing critic NN structure and then the approximated optimal control policy can be derived. The closed-loop manipulator system is proved to be asymptotic stable by using the Lyapunov theory. Finally, simulation results are provided to demonstrate the effectiveness and advantages of the proposed control method.

Development and Evaluation of a Prosthetic Ankle Emulator with an Artificial Soleus and Gastrocnemius

In individuals with transtibial limb loss, a contributing factor to mobility-related challenges is the disruption of biological calf muscle function due to transection of the soleus and gastrocnemius. Powered prosthetic ankles can restore primary function of the mono-articular soleus muscle, which contributes to ankle plantarflexion. In effect, a powered ankle acts like an artificial soleus. However, the biarticular gastrocnemius connection that simultaneously contributes to ankle plantarflexion and knee flexion torques remains missing, and there are currently no commercially-available prosthetic ankles that incorporate an artificial gastrocnemius. The goal of this work is to describe the design of a novel emulator capable of independently controlling artificial soleus and gastrocnemius behaviors for transtibial prosthesis users during walking. To evaluate the emulator's efficacy in controlling the artificial gastrocnemius behaviors, a case series walking study was conducted with 4 transtibial prosthesis users. Data from this case series showed that the emulator exhibits low resistances to the user's leg swing, low hysteresis during passive spring emulation, and accurate force tracking for a range of artificial soleus and gastrocnemius behaviors. The emulator presented in this paper is versatile and can facilitate experiments studying the effects of various artificial soleus and gastrocnemius dynamics on gait or other movement tasks. Using this system, it is possible to address existing knowledge gaps and explore a wide range of artificial soleus and gastrocnemius behaviors during gait and potentially other activities of daily living.

Adaptive Impedance Control of a Novel Automated Umbilical System for Propellant Loading

In this paper, an automated umbilical system based on a 6-dof (degree of freedom) hydraulic parallel mechanism is proposed to automate the rocket propellant loading process. The mechanical structure, vision acquisition algorithm, and control algorithm used in the system are described in detail in the paper. To address the fluid nonlinearity problem of the hydraulic drive system, nonlinear compensation and three-state feedback control are used in the paper to enhance the performance of the hydraulic system. For the problem of force tracking during the docking process between the umbilical system and the rocket, an adaptive impedance control algorithm based on the online environmental parameter estimation is proposed in the paper, which effectively reduces the contact force during the docking process. The dynamic tracking and docking experiments indicate that this automated umbilical system features rapid reaction speed, high measurement precision, and good flexibility, which can be used to realize the auto-mating and following task for the propellant loading robot in a hazardous environment.

Application of Adaptive and Switching Control for Contact Maintenance of a Robotic Vehicle-Manipulator System for Underwater Asset Inspection

The aim of this study is to design an adaptive controller for the hard contact interaction problem of underwater vehicle-manipulator systems (UVMS) to realize asset inspection through physical interaction. The proposed approach consists of a force and position controller in the operational space of the end effector of the robot manipulator mounted on an underwater vehicle. The force tracking algorithm keeps the end effector perpendicular to the unknown surface of the asset and the position tracking algorithm makes it follow a desired trajectory on the surface. The challenging problem in such a system is to maintain the end effector of the manipulator in continuous and stable contact with the unknown surface in the presence of disturbances and reaction forces that constantly move the floating robot base in an unexpected manner. The main contribution of the proposed controller is the development of the adaptive force tracking control algorithm based on switching actions between contact and noncontact states. When the end effector loses contact with the surface, a velocity feed-forward augmented impedance controller is activated to rapidly regain contact interaction by generating a desired position profile whose speed is adjusted depending on the time and the point where the contact was lost. Once the contact interaction is reestablished, a dynamic adaptive damping-based admittance controller is operated for fast adaptation and continuous stable force tracking. To validate the proposed controller, we conducted experiments with a land robotic setup composed of a 6 degrees of freedom (DOF) Stewart Platform imitating an underwater vehicle and a 7 DOF KUKA IIWA robotic arm imitating the underwater robot manipulator attached to the vehicle. The proposed scheme significantly increases the contact time under realistic disturbances, in comparison to our former controllers without an adaptive control scheme. We have demonstrated the superior performance of the current controller with experiments and quantified measures.