Research On Power-assisted Full-body Exoskeleton Robotic System Based On Flexible Drive

In recent years,Ministry of Civil Affairs of the People's Republic of China announced a social service development statistics bulletin 2016.The report shows that by the end of 2016,the country's population aged 60 and above has reached 230 million,which accounts for 16.7% of the total population,China is already the world's most elderly populous country.More and more elderly people are with declining body functions.Additionally,the elderly and the disabled problems have aroused the attention of the Chinese goverment.Intelligent wheelchair is one kind of typical intelligent service robot that can help elderly people's action,Most of these people can only use a wheelchair to achieve self-care.Walking and standing are their greatest desire.Exoskeleton robot is a new kind of wearable intelligent robot developed in recent years,Wearers and exoskeleton robots need to work together,exoskeleton robots provide support and strength just like the bones in our bodies,the robot can help the wearer stand,walk and improve the performance of the upper limb.Which greatly enhances the wearer's function to complete the daily work.The exoskeleton robot can indeed improve the quality of life of patients and the elderly.There is a very high coupling relationship between exoskeleton robot and wearer,they are not independent individuals.Exoskeleton robots need to read various signals in a very short time and accurately judge the wearer's true motion intention,and then the corresponding decision is made based on the prior information and the intention.The control strategy base on physical sensors signals has many advantages,therefore,it is widely used by many research institutions in recent years.Most target wearers of the exoskeleton robot are lack of power.The existing means of control are difficult to achieve free walking and other actions.The biological signals such as electroencephalograph(EEG)and electromyography(EMG)can more quickly reflect the wearer's motion intention,but the EEG signal and physical force,position feedback signal fusion research has not yet achieved breakthrough results.So researchers are still needed to continue their efforts.In this dissertation,several common problems of different exoskeleton robot system are deeply studied.The main research results and contributions are as follows:(1)The advantages and disadvantages of different kinds of exoskeleton robots were compared and analyzed.The joint arrangement and the degree of freedom of the exoskeleton were assigned according to the physiological structure of the human limb,A novel exoskeleton robot based on flexible drive was designed,This design greatly reduces the complexity of the exoskeleton robot transmission structure,and we can put the drive unit in the robot's control backpack,which makes the robot's body more compact and delicate.(2)In this dissertation,the kinematics model of the full-body exoskeleton robot was established base on D-H method,it also established the pose mapping of the human body's posture and exoskeleton robot.Based on this model,the inverse kinematics model of general gait was derived.We also studied some important parameters and performance of the dynamic system.Finally,based on the Adams simulation software environment,the parameters of some important parts of the skeleton robot in the flat walking were calculated,The influence of gait parameters on driving force was revealed,which provides effective reference for robot control system design and the optimization design of the exoskeleton robot.(3)The key measurement techniques and feature extraction of human gait are studied in this dissertation,the purpose of this study is to improve the gait and movement measurement techniques for exoskeleton.In this dissertation,two kinds of gait and action information collection system were established.Eight kinds of movement and gait database of 30 people are built based on the two gait acquisition systems.Three kinds of machine learning methods are used to analyze the time series signal of the eight kinds of movement and gait.Finally,the results are compared and analyzed after experiments.In this dissertation,a method of automatic recognition based on multi-layer perceptron algorithm was also proposed to find the most suitable individual gait.Which lays a solid foundation for the realization of human-machine coupling control.(4)A control strategy for exoskeleton robot based on hybrid scene switching was proposed in this dissertation.A simple and efficient sensor system was designed for exoskeleton robot,a new gait and intelligent fuzzy control strategy was established based on multisensor information fusion.The adaptive manipulation of exoskeleton robot was realized by reinforcement learning.The robot controller guided the execution of the control system and used the local motion planner to perform gait and motion planning.A precise gait and motion planning method and a dynamic gait planning method based on s tability threshold were proposed.Finally,experiments were carried out to validate our strategy and algorithm.