Control Of Table-Placed Rehabilitation Robot For Upper Limbs

Stroke is one of the leading causes of motor function disability in adults, and makes greatinconvenience in patients’ daily life. Normally, patients need rehabilitation with the help oftherapist. Rehabilitation robot is the combination of robotic technology and clinical therapy,which can help disable patients to regain their motion functions. Comparing with manual therapy,the usage of rehabilitation robot could shorten therapy time, improve the motion performance,and release the therapist from physical work. In the meanwhile, the measured forces andpositions during the training supply the quantitative assessment of neuro-motor state of patientsand their progress, which is useful for further therapy and research.In this dissertation, the development and progress of rehabilitation therapy is described, andthe state and process of rehabilitation robot is analyzed, and the system is validated in theexperiments. After the comparison and analysis of structures, control strategies, and clinicalresults of exiting upper-limb rehabilitation robots, a new table-placed active rehabilitation robotsystem is proposed and designed based on the demands of upper-limb rehabilitation.In this research work of upper-limb rehabilitation robot, the hardware and software systemsare established, and the control strategies and methods are designed and utilized. In this thesis,the sensor fusion method, position controller and haptic controller are mainly discussed in details.The main innovations and works are listed as following.1．A new table-placed active rehabilitation robot system is proposed and designed on anomni-directional mobile robot, and is able to provide planar3degrees of freedom of activerehabilitation training for arm and shoulder. This system also support the motion training inhome environment, is to increase the training time and intensity, and reduce cost the relatively.2．Pointed to the larger size of normal three wheel omni-directional platform, a newarrangement of regular triangle omni-directional platform to decrease the size, and thekinematics and dynamics of the robot are derived.3．To get the estimation of robot position, a sensor fusion scheme is designed based onKalman filter. This method combines an optical absolute position measurement with wheel speedinformation, processed by a discrete kinematic model, which is to convert the wheels speed tothe translational and rotational velocity. As a result of this approach, the testing with actualsensors has proved that the utilized scheme is possible to estimate the position and orientation in real time.4．A cascaded position controller is designed for the mobile robot to allow for arbitrarytranslational reference motion. In inner control loop，motor model has been built, and threeindividual PI controller has been implemented to control the motor speed. For the outer loop, astate-space model is constructed based on kinematic model and speed model, and multi-variablecontrol design is utilized by a discrete-time linear quadratic regulator. The position controlsystem is validated in experiment and the results satisfy the haptic control and rehabilitationdemands.5．To offer compliance in motion training, the haptic strategy is considered and analyzed. Inthis research, haptic control was realized in form of an admittance control scheme whichtransfers the measured interaction force to a reference motion through a virtual admittance. Afurther virtual therapist is designed to assist patient to accomplish the tracking during training.The haptic controller including the virtual therapist has been successfully tested in experimentswith neurologically intact subjects.