Design And Research Of Autonomous Obstacle Avoidance Upper Extremity Exoskeleton Robot System

With the intensification of social aging,the proportion of the population with cardiovascular and cerebrovascular diseases is also increasing.The brain nerves of these patients cannot normally control limb movements,and help patients to perform rehabilitation exercises to stimulate the brain nerves to re-establish contact with limbs It is the mainstream treatment method,but the current corresponding medical resources are very limited.The upper limb exoskeleton robot is a wearable mechanical device that pulls the patient's upper limb for rehabilitation.Its movement is similar to the upper limb of the human body.In recent years,it has been increasingly used in medical rehabilitation.Therefore,the study of upper limb exoskeleton robots capable of autonomous obstacle avoidance has broad application prospects and scientific research value in rehabilitation equipment.Through the research and analysis of the development status of the upper extremity exoskeleton robot at home and abroad,combined with the needs and indicators of patients' rehabilitation training,the overall design of the upper extremity exoskeleton robot is completed.In terms of structure,an upper limb exoskeleton robot with a seven-degree-of-freedom dual-arm isomorphic mechanical arm was designed according to the movement of the human upper limb;in order to achieve robot trajectory planning and joint control,designed a control system for upper limb exoskeleton robot based on ROS platform.Kinematics and dynamics analysis of the designed extremity exoskeleton mechanical arm.The upper extremity exoskeleton kinematics model based on the DH parameter method was established,and its positive kinematics analysis was completed.The robotics toolbox was used to verify the correctness of its kinematics model.The mechanical model improves the calculation efficiency of the driving torque of the exoskeleton joint,and the joint driving torque obtained by the space operator algebra is verified by the ADAMS software,which provides a theoretical basis for joint control.In order to achieve autonomous obstacle avoidance for upper exoskeleton robots,an autonomous obstacle avoidance algorithm based on point cloud information is proposed.According to the depth point cloud information collected by Kinect andRGB images,a spatial cost map is established,and the OBB bounding box algorithm is used as a collision detection algorithm;in order to enhance the calculation efficiency of the path planning algorithm,the artificial potential field method is introduced as the direction on the basis of the RRT path planning algorithm Guide function,and build a space cost map containing obstacles in Matlab,and carry out obstacle avoidance simulation research on the extremity exoskeleton robot to verify the feasibility of the algorithm.Finally,for the prototype of the extremity exoskeleton robot,a control system based on the ROS platform was developed.In order to improve the response speed of the upper exoskeleton robot to the planned trajectory,an auto disturbance rejection controller with dynamic feedforward compensation was designed to achieve the rapid response of each exoskeleton joint to the target planned trajectory.On the basis of the ROS development platform,the design of the upper limb exoskeleton robot control system was completed,and joint simulation with Gazebo was carried out.The experimental results show that the designed RRT algorithm with artificial potential field method has a reasonable path planned in the environment containing obstacles,and the trajectory tracking of the auto disturbance rejection controller with dynamic feedforward compensation is good and can control Gazebo.The upper extremity exoskeleton model in the model achieves autonomous obstacle avoidance.