Adaptive task-space tracking for robot manipulators with uncertain kinematics and dynamics and without using acceleration

In this paper, we consider the task-space tracking problem for robot manipulators with uncertain kinematics and dynamics. Imprecise kinematic parameters would cause errors in the solution of inverse kinematics, and the closed-loop system remains nonlinear and coupled. At the same time, task-space velocity or joint acceleration are usually required, which implies an increase of the production cost. Therefore, an adaptive control method is proposed, neither task-space velocity nor joint acceleration are needed. The measurement of task-space velocity is avoided using a low-pass filter, and by defining a second order reference trajectory, the joint acceleration is also eliminated. Using Lyapunov theory, we have proved that the end-effector tracking errors can asymptotically converge to zero. Examples and numeral simulations are provided to validate the effectiveness of the proposed tracking method.