In order to apply the TOUR model, you have to define what you mean by locally distinctive place, write programs so that the robot can recognize that it is in an LDP, and be precise about what constitutes an arc between two nodes in a graph of locally distinctive places. Actually implementing a system that can reliably recognize locally distinctive places and traverse the space between them is more difficult than you might imagine. Behavior-Based Spatial Reasoning One difficult part of programming robots is trying to figure out what a robot should do given what a robot can perceive about its environment. Writing robot programs is particularly difficult when the robot perceives its environment in very different ways than the programmer perceives that same environment. Behavior-based methods generally avoid internal representations of any sort, arguing that they are unnecessary for most purposes.
Maps are obviously useful to robots that have to navigate from one place to another.
Maya Mataric's Masters thesis was about getting a behavior based-robot to learn maps and plan paths. You can read about the details in her clearly written thesis, but the basic idea is simple and can be extended in a variety of ways. Typically behaviors are initiated by specific signals, e.g., innate releasing mechanisms, which can be generated externally or as a result of other behaviors. Sequences of such behaviors can be initiated when one behavior terminates by generating the stimulus or releaser for the next in the sequence. Suppose you let a robot designed to explore its environment just run for a while.