Qualitative Sonar Based Environment Learning for Mobile Robots

摘要

We present a method for navigation and environment learning based on active sensing using sonar and a compass. The method consists of a set of incrementally designed behaviors for extracting environment features from the sensory data. The features are stored in a totally distributed list of augmented finite state machines which serves as a decentralized world model.