"Robotic Mapping and Exploration" is an important contribution in the area ofself-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 rangeof mobile robots and field settings, such as search and rescue, transportation tasks, or automated vacuum cleaning. Recent research in the area of self-localization and mapping (SLAM) for autonomous robots The presented solutions include uncertainty-driven exploration, active loop closing, coordination of multiple robots, learning and incorporating background knowledge, and dealing withdynamic environments Accompanied by a rich set of experiments INDICE: Introduction.- Basic Techniques.- Part I Exploration with Known Poses.- Decision-Theoretic Exploration Using Coverage Maps.- Coordinated Multi-Robot Exploration.- Multi-Robot Exploration Using Semantic Place Labels.- Part 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.
- ISBN: 978-3-642-01096-5
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 195
- Fecha Publicación: 01/05/2009
- Nº Volúmenes: 1
- Idioma: Inglés