A Motion Control Method for Robotic Arm Based on a Wearable Hybrid Human-Machine Interface
Existing HMI(human-machine interface)systems suffer from issues such as limited commands,complex oper-ation,and restricted task capabilities,preventing effective expansion into multi-dimensional motion control for robotic arms.This paper introduces a method for controlling robotic arm movements based on a wearable hybrid HMI.This method com-bines various signals,including electrooculography(EOG),head posture,and speech from the user,transforming them into control commands,thereby enabling continuous two-dimensional(2D)and three-dimensional(3D)motion control of the robotic arm at any angle.10 participants complete tests involving command output,2D target tracking,alphabetic writing,and 3D object grasping.The results indicate that the blink-generated commands of the proposed system have an average accuracy of 96.67％,an average response time of 1.51 s,an average information transfer rate(ITR)of 142.53 bit/min,and an average false positive rate(FPR)of 0.05 event/min.Additionally,the root mean square deviations of target tracking along 2 different routes on a 2D plane are 0.12 and 0.14(normalized),while the average trajectory efficiency of 3D object grasping is 92.65％.The control performance of the system is comparable to manual control.The experimental results verify the fea-sibility of using a hybrid HMI for achieving efficient motion control of robotic arms and its potential application in assisting upper-limb mobility functions.
hybrid human-machine interfacewearable devicerobotic armmotion control
万方数据
维普
