Environment classification using Kohonen self-organizing maps
This paper describes a new method for classifying three-dimensional environments in real time using Kohonen self-organizing maps (SOMs). The method has been developed to enable autonomous underwater vehicles (AUVs) to navigate without human intervention in previously unexplored subsea environments, but can be generalized to unmanned aircraft equipped with appropriate sensors flying over unchartered terrains, or spacecraft exploring remote planets, subject to appropriate pre-mission training. The method involves a fuzzy comparison between a SOM created in real time using accumulated sensor data and a class atlas of SOMs derived from previously trained and manually classified environments. This enables mission- and environment-appropriate AUV navigation strategies to be selected in real time. Simulation results using real-world, three-dimensional environment data acquired from digital elevation maps are presented, which demonstrate the potential of the method.
kohonen self-organizing maps autonomous underwater vehicles robot control architectures terrain classification