Renpeng Tan

Adaptive controller for omni-directional walker: Improvement of dynamic model

An omni-directional walker (ODW) is being developed for both walking rehabilitation and walking support for people with walking disabilities. The ODW cannot accurately follow a training path planned by a physical therapist for walking rehabilitation due to the center-of-gravity shifts and load changes caused by users. To address this issue, a new center-dynamic model of the ODW is derived considering center-of-gravity shifts and load changes. An adaptive control method is shown. Comparison with a dual-loop proportional-integral (PI) controller in simulations shows that the proposed method improves the path tracking accuracy.

Adaptive control method for path tracking of wheeled mobile robot considering parameter changes

Wheeled mobile robots are widely used in industry, agriculture, and daily human life because they have essential loading capability. Many studies about path-tracking of wheeled mobile robots have been conducted. However, the path-tracking accuracy of these robots is low due to non-linear friction in the wheels, centre-of-gravity shifts and load changes. To address these issues, this paper proposes a motion control method based on the adaptive control law for a wheeled mobile robot. This control method does not need the exact values of plant parameters and can adapt to parameter uncertainties by measuring and adjusting the parameters automatically. Therefore, it is very robust to plant parameter changes caused by non-linear friction, centre-of-gravity shifts, and load changes. To verify the effectiveness of the proposed control method, path-tracking simulations are carried out. The simulation results demonstrate the feasibility and effectiveness of the adaptive control method.

Motion control of omni-directional walker for walking support

An omni-directional walker (ODW) has been developed which can support people with walking disabilities to perform indoor walking. During walking support, the walker can identify the users directional intention according to the users forearm pressures and support the user to go in the intended direction. In this paper, an adaptive control method is proposed to control the ODWs movement toward the direction in which the user intends to go. Simulation results show that the ODW can accurately follow the users intention direction with the proposed control method.

Study of activation in motor cortex during mental imagery of walking using fNIRS

A walking rehabilitation system is proposed which includes both muscle strength enhancement by walking rehabilitation machines and neurological rehabilitation by imaginary walking. In a previous study, we have demonstrated that the concentration of oxygenated hemoglobin (oxy-Hb) in motor area during imaginary walking was higher than that during real walking by means of fNIRS (functional Near-InfraRed Spectroscopy). In order to develop an effective way to activate the motor area in mental imagery, we compared the activation in motor area during real walking (RW), virtual walking (VW), and walking observation (WO). In the VW, subjects were shown moving scenes of a virtual visual environment in which subjects easily imagined as if they were actually walking from the first-person perspective. In the WO, subjects were instructed to imagine that they were walking with the same pace to a person in the video being shown to the subjects (third-person perspective). Four subjects participated in the experiment. As a result, the oxy-Hb in motor area during both VW and WO were higher than that during RW on the average. This was because that it was not necessary to pay attention to the movements of the legs and feet during normal walking, while movement planning was required when the subjects imagined their walking in the same way to another person. There was no significant difference between the oxy-Hb during VW and that during WO. The importance of stimulus diversity in mental imagery of walking was suggested.

Path tracking control of an omni-directional walker considering pressures from a user

An omni-directional walker (ODW) is being developed to support the people with walking disabilities to do walking rehabilitation. The training paths, which the user follows in the rehabilitation, are defined by physical therapists and stored in the ODW. In order to obtain a good training effect, the defined training paths need to be performed accurately. However, the ODW deviates from the training path in real rehabilitation, which is caused by the variation of the whole systems parameters due to the force from the user. In this paper, the characteristics of pressures from a user are measured, based on which an adaptive controller is proposed to deal with this problem, and validated in an experiment in which a pseudo handicapped person follows the ODW. The experimental results show that the proposed method can control the ODW to accurately follow the defined path with or without a user.

Comparison of Cortical Activation During Real Walking and Mental Imagery of Walking - The Possibility of Quickening Walking Rehabilitation by Mental Imaginary of Walking

Non-invasive brain imaging technologies have become an increasingly important part of research in neurosciences. The thirst for information about brain function is universal, and imaging of the human brain has been used by many as a medium for the discussion. So far, Functional brain imaging with positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalographic (EEG), and Magnetoencephalography (MEG) have greatly increased scientists’ ability to study localized brain activity in humans and carry out studies for better understanding of the neural basis of mental states. They have been used extensively to map regional changes in brain activity, not only in neuroscience researches, as well as in social sciences to objectively and quantitatively evaluate psychological problems. PET and fMRI are based on changes in local circulation and metabolism (Raichle & Mintun, 2006). PET produces detailed three-dimensional images of certain processes in the brain by detecting gamma rays emitted indirectly by radioactive material which has been injected into the person’s blood stream prior to scanning. fMRI produces high quality pictures of the brains delicate soft tissue structures using strong magnets and pulses of radio waves to manipulate the natural magnetic properties of hydrogen, creating useful images of organs and soft tissues. MEG and EEG image electrical activity in the brain. MEG measures magnetic fields generated by small electrical currents in neurons of the brain using arrays of SQUIDs (superconducting quantum interference devices). EEG uses multiple electrodes fixed to the person’s scalp to measure the dynamic pattern of electrical fields in the brain. In cognitive neuroscience, researchers use EEG technology to study event-related potentials (ERPs)—brain measurements that are associated with a response to a stimulus.

Car-like mobile robot oriented digital acceleration control method

Car-like mobile robots are widely used in industry, ports, and agriculture because they have the necessary loading capability. So far, the path tracking accuracy of these robots is low due to nonlinear friction in the wheels, center-of-gravity shifts, and load changes caused by users. To address these issues, a dynamics model is derived that considers nonlinear friction, center-of-gravity shifts, and load changes. In particular, a digital acceleration control algorithm is proposed to compensate for nonlinear friction. Simulations are executed using proportional-integral (PI) control for comparison with those using the proposed method. The results demonstrate the feasibility and effectiveness of the proposed digital acceleration control method.

Adaptive control of an omni-directional walker considering the forces caused by user

An omni-directional walker (ODW) has been developed to support people with walking impairment to do walking training without the presence of a physical therapist. In order to get a good training effect, the ODW needs to precisely follow the training path which is defined by a physical therapist. However, the forces caused by user make the ODW deviate from the training path. In previous studies, an adaptive controller was developed to deal with the pressure leading to the load change and center of gravity shift of the ODW. However, the forces from used consist of both vertical pressure and horizontal thrust. In this paper, an improved model is proposed considering both the pressure and the thrust. Furthermore, an adaptive controller is designed based on the model to improve the path tracking accuracy. The simulation is carried out and the results demonstrate that the proposed method is effectiveness to control the ODW following the training path accurately.

An improved adaptive controller with parameter optimization by GA for an omni-directional walker

An omni-directional walker (ODW) has been developed for walking rehabilitation for people with walking disabilities. In re habilitation, a user needs to accurately follow the reference path stored in the ODW in order to obtain good training effect. In order to improve the path tracking accuracy, a nonlinear adaptive controller was developed in pervious studies, to deal with load change and center of gravity shift caused by the user. The path tracking accuracy can be improved by adjust the parameter of the adaptive controller. In this paper, genetic algorithm is used to automatically and quickly optimize the parameters of adaptive controller. Simulation was conducted, in which the ODW was controlled to follow a linear path. The results were shown that the parameter optimization strategy is effective to quickly find the optimal parameter.

Digital acceleration controller based on recursive least squares (RLS) identification for an excretion care support robot

In previous studies, an excretion care support robot has been developed for the bedridden people. To improve the motion performance for the robot, a digital acceleration controller has been designed to deal with the problem of uncertain and unbounded nonlinear friction. The motion performance of the digital acceleration control system is not sufficient because the design of the digital acceleration controller need the exact values of the plant parameters of the robot. However, these values are variable due to center-of-gravity shifts and load changes. In this paper, to address these issues, a discrete-time system identification method using recursive least squares(RLS) algorithm is proposed to identify the parameters of the plant online. This method is effective to deal with the problem of center-of-gravity shifts and load changes. Simulations are conducted, the results demonstrate the feasibility and effectiveness of the proposed control method by comparing it with the digital acceleration controller without RLS.