This paper presents and discusses a neuromorphic approach to designing a control law for locally guided robot navigation which allows for instantaneous response to the changes in the robot environment. The control algorithm is defined in the discrete domain appropriate for dedicated VLSI implementation and direct processing of discrete sensory data, such as obtained from a CCD camera. The control law is based on the principle of virtual force fields. The virtual forces (repulsive and circulation vectors) guiding the robot in the vicinity of obstacles are derived from the gradient fields associated with discrete representation of visual information. Discretization and computational tasks are assigned to parallel neuromorphic processors, which emulate the gradient operations. The particularities of discrete geometrical representations of the world and the adjustable control parameters essential for flexible and robust controller operation are discussed in detail. Finally, a detailed scheme of a tunable navigation controller specifying the parameters generated internally by the network and those that have to be provided from an external source (e.g., the operator, or a supervisory knowledge-based controller) is provided.