未知人体作业环境下基于力信息的机器人法向姿态跟踪方法OA

In human-robot interaction scenarios such as medical rehabilitation and cosmetic care,a robot must maintain a stable contact posture normal to the skin surface.Uncertainties from inter-individual differences,varia-tions in working areas,posture changes during the process,and real-time deformation severely limit the robot's abi-lity to track the flexible curved contours of the human body.To solve this problem,multiple auxiliary coordinate frames are established on the force-motion interaction system,the kinematics as well as the force/torque relation-ships during the contact are described and analyzed,and the corresponding transformation matrices of the coordi-nate frames are constructed.By combining Hertzian elastic contact theory with a biomechanical adhesion-friction model,a normal-vector relationship model based on six-axis force information is developed for a rigid spherical end-effector interacting with soft tissue,which is then used to obtain the current normal attitude in real time.To ensure the accuracy of the six-axis force data,a dual compensation scheme integrating secondary gravity compensation with periodic torque-error compensation is implemented.The proposed method enables real-time tracking of the un-known surface normal posture of human soft tissue through force-sensor feedback.Finally,experiments on a facial model,tracking the trajectory from the glabella to the nose tip along the nasal dorsum,are carried out.The results demonstrate that the normal-attitude error remains within 1.12°～3.20°under an impedance controller that regulates a compliant normal force,meaning that the proposed control strategy is effective and is helpful to enhance the adap-tability of robots in unknown human working environments.