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"Robotic Mapping and Exploration" is an important contribution in the area of simultaneous localization and mapping (SLAM) for autonomous robots, which has been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the autonomous mapping learning problem. Solutions include uncertainty-driven exploration, active loop closing, coordination of multiple robots, learning and incorporating background knowledge, and dealing with dynamic environments. Results are accompanied by a rich set of experiments, revealing a promising outlook toward...

This book constitutes the proceedings of the 8th International Conference on Spatial Cognition, SC 2012, held in Kloster Seeon, Germany, in August/September 2012. The 31 papers presented in this volume were carefully reviewed and selected from 59 submissions. The conference deals with spatial cognition, biological inspired systems, spatial learning, communication, robotics, and perception.

Autonomous navigation is an essential capability for mobile robots. In order to operate robustly, a robot needs to know what the environment looks like, where it is in its environment, and how to navigate within it. Particle Filters for Robot Navigation summarizes approaches that address these three problems and that use particle filters as their main underlying model for representing beliefs. It illustrates that these filters are powerful tools that can robustly estimate the state of the robot and its environment and that they are also well-suited to making decisions about how to navigate in...