In this paper we have presented a novel technique for the navigation and path formulation of wheeled mobile robot. In a given environment having obstacles, a path is generated from the given initial and final position of the robot. Based on the global knowledge of the environment a global path is formulated initially. This global path considers all the known obstacles in the environment and must avoid collision with these obstacles, i.e. the formulated path must be safe (collision free). For global path formulation strategic schemes have been employed using the a priori knowledge of the environment. The global path is fed to the robot. When unknown obstacles come in the path of the robot, it must deviate from the given global path and should generate a local path to avoid collision with the new unknown obstacle. By using sensors data the reactive schemes have been implemented for local path formulation. For local path formulation the path has been subdivided into intermediate steps known as sub goals. In the existing approaches known and unknown objects are considered separately. But in some of the practical applications known and unknown objects need to be considered simultaneously. This paper considers the problem of robot motion formulation in an environment having already known obstacles and unknown new moving objects. A Novel algorithm has been developed which incorporates local path planner, optimization and navigation modules. As unknown objects can appear in the environment randomly therefore uncertainty in the environment has been considered.