Research On The Human Intention Recognition And Motion Control For The Lower Exoskeleton Robot

Exoskeleton robot is a wearable smart device,which can enhance the motion ability of human beings,has broad application prospects in the fields of military,medical and civil disaster relief.As an important part of exoskeleton robot,the power-assisted lower limb exoskeleton has been a research hotspot,where the related technologies are increasingly developing.However,how to realize the human-machine interaction of the exoskeleton and the wearer is still an urgent issue to be solved.Therefore,taken the power-assisted lower exoskeleton as the research object,the mechanical system,intention recognition system and control system are studied in-depth in this thesis,especially the gait event based human intention recognition algorithm designed in the intention recognition system,which provides a new idea for the exoskeleton robot to identify the wearer's intention.The specific research contents of this paper are as follows:Chapter 1 expounds the research background and significance of this work,investigates the research status and achievements of exoskeleton robots at home and abroad,and summarizes the existing achievements from the aspects of mechanical system,intention recognition and control methods,where the advantages and disadvantages are analyzed in details.Finally,the innovation and main research contents are clarified.Chapter 2 studies the kinesiology of the human body's lower limbs,and introduces the definition of the human body's reference axis,datum plane and gait cycle.According to the CGA gait database,the parameters of the lower limb exoskeleton are determined,and the structure of the lower limb exoskeleton is designed,including the waist and leg.Finally,the strength checking for the key parts of lower limb exoskeleton is conducted based on ANSYS,which verifies the reliability of the structure and lays the foundation for the subsequent prototype experiment.Chapter 3 builds the experimental platform of intention recognition system,where the various types of sensors are determined,and the data acquisition circuit is designed to realize the initial collection of sensor data.A gait-event-based human intention recognition algorithm and a human-machine-interaction-based impedance model are proposed respectively,the intention recognition algorithm achieves the function of the simultaneous step frequency and stride adjustment of standard trajectory,and the human-machine-interaction-based impedance model improves the real-time performance of recognition and outputs the target trajectory.Chapter 4 introduces the experimental platform of the control system,where the NI CompactRIO embedded system and C-series modules are used to form the main controller of the exoskeleton,which is mainly responsible for sensor data acquisition,human intention recognition,real-time motion control and other tasks.A forward kinematics model of the lower limb exoskeleton is then established,and a PI-based position controller is designed for the single joint of lower limb.Chapter 5 implements the experiment the lower limb exoskeleton prototype,which includes the verification of human intention recognition and control algorithm,and the walking experiment of the lower extremity exoskeleton.In the experiment of human intention recognition algorithm verification,the adjusted standard joint trajectory is obtained based on the IMU and foot pressure sensor data,and the effectiveness of the algorithm is verified from the experimental results.In the experiment of control algorithm verification,the real joint tracking trajectory is obtained and the effectiveness of the algorithm is verified.Finally,in the wear walking experiment,it can be seen that the exoskeleton designed in this thesis can realize the synchronous movement with the human body.Chapter 6 summarizes the work and results of the thesis,puts forward the inadequacies of the exoskeleton,and prospects the prototype development in the future.