Robot navigation in indoor environments is usually organized as two complementary activities, local displacement control and global path planning. Both activities have to be connected across different space and time scales in order to obtain a smooth and responsive system that follows the path but adapts to the unforeseen situations imposed by the real world. There is not a clear consensus in how to do this and some important problems are still open. In this paper we propose a new navigation stack in which algorithms working at different time and space scales are connected through a dynamic data structure representing the current path. We use the concept of elastic band proposed by [] and integrate it as the core shared representation of a set of concurrent processes, to obtain a smooth trade off between responsiveness and target following. A set of experiments are presented with the robot Sheldon in indoor environments.