Research On Human-Robot Coordination Control Strategy Of Lower Limb Exoskeleton Based On Interactive Information Perception

With the growing of social aging population,the weakening of regular exercise capacity and the occurrence of potential safety accidents caused by the decline of physical function have increased the families’ economic burden and strained the nation’s medical resources.Lower limb exoskeleton robot,as a wearable exercise auxiliary device,has unique advantages in assisting the weak and normal people to complete daily activities,reduce physical consumption,and improve the quality of life.Therefore,the development of a lower-limb exoskeleton robot that can assist the normal movement and safety protection of the weak and norm al people will help improve the level of technological informatization in production and life,promote the construction of a smart aging society,enhance the people’s quality of life,and strengthen the build of social modernization,which has a very positive and important meaning.Based on the developed lightweight lower extremity exoskeleton system,this paper is mainly dedicated to the research on the interactive information perception among human,robot,environment,and the coordinated control strategy between human and robot.To solve the problem of gait perception during different daily activities,a multi-class identification method of locomotion modes based on the fusion of multi-modal information of the exoskeleton itself and a multi-class identification method of gait phases based on the time-space feature fusion of the wearer’s foot contact matrix are designed,so as to realize the gait identification and feature switching.To satisfy the requirement of follow-up of flexible motion in swing phase,an impedance controller with dynamically adjustable parameters based on fuzzy self-adaptation is designed to track the human intended motion.To satisfy the requirement of assistance of gravity overcoming in support phase,a traction controller guided by the target potential energy point is designed to provide additional assistance to the stretched joint.Thereby,the gait phase in a specific locomotion mode can be controlled synergistically in a targeted manner.To solve the problem of imbalance perception under external disturbance,the phenomenon that the early balance adjustment of the passive-ankle exoskeleton is mainly dominated by the wearer is taken into account,the boundary condition of valid foot support region is revised,and the balance state manifold based on the intervention of the wearer’s ankle joint is designed.The dynamic balance stability criterion of the human-robot integrated system(HEIS)is established,enabling the exoskeleton to predict the balance perception of human body.To satisfy the requirement of posture adjustment of balance recovery,the convergence characteristics of motion state of center of mass(Co M)in the dynamic balance domain are analyzed,the virtual imbalance potential energy is designed to represent the degree of deviation of Co M from the boundary of the dynamic balance domain,and the minimum modulation decoupling mapping function based on the characteristics of zero dynamic is established.Thereby,the targeted planning acceleration equation in the joint variable space is solved,and the balance recovery control of HEIS is realized.To solve the problem of terrain perception in the multi-obstacle environment,the separation procedure of point cloud subsets to be processed which integrates voxel-grid downsampling,vector-unconstrained maximum correlation plane fitting,statistical outlier removal denoise filter,and multi-class Euclidean clustering is designed,which achieves the adaptive and independent distinguishment of multiple obstacles under the premise of unknown terrain information.A compact spatial bounding box model based on the closeness regression of 2D minimal bounding rectangle and the synchronous convergence of 3D minimal cuboid features is established,and the sectional feature terrain in the sagittal plane of swing leg is reconstructed.To satisfy the requirement of avoidance and guidance during obstacle crossing,the state function and cost function based on whole-body kinematics are designed,the stability constraints and collision-free constraints for different gait stages in the gait transition process are established,and the switching conditions for segmented planning of nonlinear model predictive control based on intermediate interpolation inflection points and gait stages are introduced.Thereby,the synchronous correction of the distances between the swing sole and the obstacles or the target landing point is achieved.On the basis of simulation analysis,experimental tests are conducted on HEIS,which have verified the effectiveness of the motion control in level walking,squatting and stair climbing,the effectiveness of balance recovery control under external disturbance,and the effectiveness of obstacle crossing control in the multi-obstacle terrain.The experimental results show that the interactive information perception method and human-robot coordinated control strategy proposed can realize the motion assistance and safety protection for the wearer.