The aim of this study is to assess the feasibility of an approach for generating velocity-dependent trajectories to train neurologically injured patients. The reference trajectories are constructed based on the gait patterns of subjects walking on a treadmill. By extracting key events (parameters) from these trajectories, the velocity dependency of the parameters is determined by regression analysis. Then, splines are fitted through these points to obtain gait patterns (position, velocity and acceleration) for specific walking velocities. Considering the severely injured patients, a feedforward controller is used in addition to the impedance controller. The approach is implemented on the LOPES gait rehabilitation robot and evaluated on healthy subjects. Results indicate that the subjects can walk naturally in the robot with the constructed reference trajectories. Further improvements to the technical design and additional testing of healthy and impaired subjects are required to show whether this approach can be transferred to clinical domain.

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The virtual torque control is a relative effective control law for the lower extremity carrying exoskeleton robot, which needs no direct measurements from the pilot or the human-machine interface, but it needs the exact mass properties and its PD controller is not applicable for the serious nonlinear system. To overcome these defaults, the virtual prototyping software ADAMS is introduced to model the exoskeleton and the model is also used to the neural network (NN) dynamic mathematics model study. At the same time, the NN is used to the dynamic feed-forward controller to compensate the human-machine interaction force. Theoretical analyse and simulation results test the feasibility and validity of this control method.

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A deformable non-uniform rational B-spline (NURBS) based volume is programmed for the Iowa State University (ISU) force-reflecting exoskeleton haptic device. A direct free-form deformation (DFFD) technique is applied for realistic manipulation. In order to implement real-time deformation, a nodal mapping technique is used to connect points on the virtual object with the NURBS volume. This geometric modeling technique is ideally incorporated with the force-reflecting haptic device as a virtual interface. The results presented in this paper introduce details for the complete set-up for a realistic virtual clay modeling task with force feedback. The ISU force-reflecting exoskeleton, coupled with a supporting PUMA 560 manipulator and the virtual clay model are integrated with the WorldToolKit (WTK) graphics display, and the results show that the force feedback from the realistic physically-based virtual environment can greatly enhance the sense of immersion.

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For robot teleoperation, a lot of research has been done to control the slave robot from a remote site using a masterarm. The concept of a distributed controller architecture for the masterarm is introduced in the paper. To reduce possible non-uniform time delay and to have higher position command update rate, the host controller with distributed satellite controllers is developed. Each satellite controller measures the corresponding joint angle, while the host controller performs initial calibration, inverse kinematics calculation, and position commands generation. The host controller and the satellite controllers are networked via a SPI (serial peripheral interface) protocol. For force feedback, the host controller solves the joint torque relations based on the kinematics of the masterarm and the satellite controller controls each joint’s torque. This distributed controller greatly reduces calculation and control loads and makes the electrical wiring very simple. In order to measure finger movement of the operator, the master hand is developed using infrared light. A similar slave satellite controller for this master hand is interfaced to the host controller via a SPI network. For teleoperation of the KIST humanoid robot which has two arms and two hands, the masterarm controller with one host controller and 16 satellite controllers is implemented. Force feedback with less than 2 msec update rate is achieved. This masterarm/hand is also integrated with a graphic model instead of using the slave robot. The experimental results show the performance of the distributed controller

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The design of a wearable upper extremity therapy robot RUPERT IVtrade (Robotic Upper Extremity Repetitive Trainer) device is presented. It is designed to assist in repetitive therapy tasks related to activities of daily living which has been advocated for being more effective for functional recovery. RUPERTtrade has five actuated degrees of freedom driven by compliant and safe pneumatic muscle actuators (PMA) assisting shoulder elevation, humeral external rotation, elbow extension, forearm supination and wrist/hand extension. The device is designed to extend the arm and move in a 3D space with no gravity compensation, which is a natural setting for practicing day-to-day activities. Because the device is wearable and lightweight, the device is very portable; it can be worn standing or sitting for performing therapy tasks that better mimic activities of daily living. A closed-loop controller combining a PID-based feedback controller and a iterative learning controller (ILC)-based feedforward controller is proposed for RUPERT for passive repetitive task training. This type of control aids in overcoming the highly nonlinear nature of the plant under control, and also helps in adapting easily to different subjects for performing different tasks. The system was tested on two able-bodied subjects to evaluate its performance.

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