More and more robotic applications are equipping robots with microphones to improve the sensory information available to them. However, in most applications the auditory task is very low-level, only processing data and providing auditory event information to higher-level navigation routines. If the robot, and therefore the microphone, ends up in a bad acoustic location, then the results from that sensor will remain noisy and potentially useless for accomplishing the required task. To solve this problem, there are at least two possible solutions. The first is to provide bigger and more complex filters, which is the traditional signal processing approach. An alternative solution is to move the robot in concert with providing better audition. In this work, the second approach is followed by introducing noise maps as a tool for acoustically sensitive navigation. A noise map is a guide to noise in the environment, pinpointing locations which would most likely interfere with auditory sensing. A traditional noise map, in an acoustic sense, is a graphical display of the average sound pressure level at any given location. An area with high sound pressure level corresponds to high ambient noise that could interfere with an auditory application. Such maps can be either created by hand, or by allowing the robot to first explore the environment. Converted into a potential field, a noise map then becomes a useful tool for reducing the interference from ambient noise. Preliminary results with a real robot on the creation and use of noise maps are presented.