Constrained motion control of robotic manipulators represents an important control task in many industrial applications. In this paper, a learning control problem is solved for simultaneous motion and force tracking of a robotic manipulator whose end-effector is in contact with the constraint environment. A robust learning control algorithm is proposed for precise path tracking of robotic manipulators in the presence of state disturbances, output measurement noises and errors in initial conditions.