This paper presents a shared-control approach for Assistive Mobile Robots (AMR), which depends on the user's ability to navigate a semi-autonomous powered wheelchair, using a sparse and discrete human-machine interface (HMI). This system is primarily intended to help users with severe motor disabilities that prevent them to use standard human-machine interfaces. Scanning interfaces and Brain Computer Interfaces (BCI), characterized to provide a small set of commands issued sparsely, are possible HMIs. This shared-control approach is intended to be applied in an Assisted Navigation Training Framework (ANTF) that is used to train users' ability in steering a powered wheelchair in an appropriate manner, given the restrictions imposed by their limited motor capabilities. A shared-controller based on user characterization, is proposed. This controller is able to share the information provided by the local motion planning level with the commands issued sparsely by the user. Simulation results of the proposed shared-control method, are presented.