Development of Magnetic-Based Navigation by Constructing Maps Using Machine Learning for Autonomous Mobile Robots in Real Environments.

Localization is fundamental to enable the use of autonomous mobile robots. In this work, we use magnetic-based localization. As Earth's geomagnetic field is stable in time and is not affected by nonmagnetic materials, such as a large number of people in the robot's surroundings, magnetic-based localization is ideal for service robotics in supermarkets, hotels, etc.

Robust and Efficient Indoor Localization Using Sparse Semantic Information from a Spherical Camera.

Self-localization enables a system to navigate and interact with its environment. In this study, we propose a novel sparse semantic self-localization approach for robust and efficient indoor localization. "Sparse semantic" refers to the detection of sparsely distributed objects such as doors and windows.