The Research On The Reactive Behavior Control Technology Of The Lower Limb Exoskeleton Robot

At present,due to the frequent occurrence of various diseases and safety accidents,the number of disabled people is increasing.In this context,the field of medical rehabilitation has entered a stage of rapid development,and lower limb exoskeleton robots have emerged.The lower limb exoskeleton robot integrates behavior and perception,enabling safe and standardized gait recovery for the patient,which can make the patients with missing lower limbs stand up again,minimizing their physical and psychological problems;For doctors,it is possible to monitor various physiological characteristics of patients in real time and achieve a more diversified treatment plan.Therefore,the development of lower limb exoskeleton robots has important practical significance.After analyzing the development status of related technologies at home and abroad,this paper conducts an in-depth study on the behavior control of lower limb exoskeleton robots.Firstly,the human gait is analyzed in detail to determine the degree of freedom required by the robot.The combination of active degree of freedom and passive degree of freedom can not only meet the needs of daily behavior,but also reduce power consumption.Based on kinematics and Vicon's three-step gait acquisition system,the information of normal human gait trajectory is analyzed,which lays the foundation for the design of control system.Secondly,the master-slave distributed control mode is determined in the reactive behavior control system.In order to collect the movement state of the lower limbs in real time,a suitable proprioceptor is selected as the sensing device of the whole system.The walking process is divided into four phases according to the plantar pressure sensor data,and the pressure multisensor data is fused by fuzzy method.The results show that the phase can be accurately identified.In the research of reactive behavior control technology,four basic behaviors are designed for the wearer: standing,sitting,walking on the flat ground and turning.Each behavior is triggered by the phase of the sensor or data fusion results.In order to make the exoskeleton robot and human body coordinate each other,ensure the continuity and naturalness of the motion process,and avoid interference,the computational torque method is used as the control algorithm for tracking.Because the inaccurate dynamics model and external disturbance will affect the control effect,this paper improves the computational torque method,and adds RBF neural network algorithm to compensate the control.At the same time,in order to ensure the stability and safety of motion and avoid secondary injury,the fall detection is based on the data of the body sensor.Using ADAMS and MATLAB joint simulation,the algorithm is verified,and the results show that the tracking effect is excellent.Finally,the hardware circuit and software of the whole system are designed to establish the communication protocol between the master controller and the slave controller.In order to verify the overall performance of the system,an experimental platform is built to verify the effectiveness of the control algorithm and behavior switching.The results show that the lower limb exoskeleton robot's reactive behavior control technology is superior.Quickly react and stabilize control when phase trigger conditions are met,and help the wearer complete the designed behavior.