Robotic Mapping and Exploration [electronic resource] / by Cyrill Stachniss.

Basic Techniques -- I: Exploration with Known Poses -- Decision-Theoretic Exploration Using Coverage Maps -- Coordinated Multi-Robot Exploration -- Multi-Robot Exploration Using Semantic Place Labels -- II: Mapping and Exploration under Pose Uncertainty -- Efficient Techniques for Rao-Blackwellized Mapping -- Actively Closing Loops During Exploration -- Recovering Particle Diversity -- Information Gain-based Exploration -- Mapping and Localization in Non-Static Environments -- Conclusion.

"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 the application to a wide range of mobile robots and field settings, such as search and rescue, transportation tasks, or automated vacuum cleaning.