In robot constrained motion problems on planar surfaces with frictional contacts, uncertainties on the contacted surface not only affect the control system performance but also distort control targets. The surface normal direction cosines are in this case uncertain parameters that are involved in both the control law and the control targets. This work proposes an adaptive learning controller that uses force and joint position/velocity measurements to simultaneously learn the surface orientation and achieve the desired goal. Simulation examples for a 6 dof robot are used to illustrate the theoretical results and the performance of the proposed controller in practical cases. (C) 2009 Elsevier Ltd. All rights reserved.