Research on Automatic Attitude Detection of Underactuated Planar Flexible Manipulator

In order to improve the dynamic analysis and control capabilities of flexible robotic arms, an automatic attitude detection method for underactuated planar flexible robotic arms based on arm angle parameterized redundant motion feature detection is proposed. Construct a DH parameter kinematic analysis model for an underactuated planar flexible robotic arm, use a fixed vector arm angle parameterization analysis method to extract the inertial features of the flexible robotic arm's attitude. Based on the DH modeling theory, the end pose modeling parameters of the robot arm were obtained. The inertia and friction parameters of the MBC controller of the robot arm were identified by the parametric redundant motion feature detection method of the arm Angle, and the arm Angle modeling of the minimum motion transformation model of the robot arm was realized, a forward algorithm for the minimum motion transformation model is designed to achieve the attitude parameter fitting control of the robotic arm. Use the arm angle parameterization method to solve the inverse kinematic model, and achieve automatic detection of the underactuated planar flexible robotic arm attitude. The simulation results show that using this method for flexible robotic arm attitude detection verifies that the inverse kinematics algorithm can solve kinematic problems of the robotic arm within a very small error range in terms of accuracy, computational efficiency, and optimal arm angle. The tracking errors of the kinematic position of the robotic arm in attitude space of the proposed method are all low, the highest is only 0.224 mm, effectively solving the algorithm singularity problem caused by the failure of arm angle definition, and improving control stability.