LIDAR sensors are a key technology for accurate world modeling. However, different LIDAR systems have different properties, and various configurations and parameter settings are possible for each system. Any project that uses LIDAR sensors must make a decision as to which sensor is used and how to configure it during integration. In many projects, these decisions are made in an ad-hoc manner based on the experience of the project managers. The question is what sensor is the best choice for a given application, and how should that sensor be mounted and configured? For example, is it better to use a single Velodyne sensor or six nodding SICKs?

To address this question we are developing a framework that allows objective comparison between alternative LIDAR configurations. Our approach is to simulate different sensor configurations and to define an objective measure of data quality for each configuration.