In this paper, we compare indirect adaptive fuzzy control and sliding-mode control in a robot manipulator application. The manipulator performs pick-and-place tasks with unknown and variable payloads. The change of payload causes large variations in the dynamics of the robot. The sliding-mode controller deals with the payload change through its inherent robustness, while the adaptive fuzzy control algorithm adjusts the controller's parameters on-line. The control methods are compared both in numerical simulations and in real-time experiments. The sliding mode controller obtains a very good steady performance. However, thanks to the continuing adaptation, the adaptive fuzzy controller eventually yields smaller steady-state error.