Where do robots get their information? For a given task, what information is actually necessary? What is even meant by "information"? These questions lie at the heart of robotics and fall under the realm of sensing and filtering. In Sensing and Filtering, the author presents an unusual view of these subjects by characterizing the uncertainty due to the many-to-one mappings between the world and sensor readings. This is independent of noise-based uncertainty...