Robot Localization

Robot localization, the process of determining a robot's position and orientation within its environment, aims to enable autonomous navigation and interaction. Current research emphasizes robust and efficient localization in challenging conditions, utilizing diverse sensor modalities (LiDAR, cameras, radar, UWB) and advanced algorithms like particle filters, neural networks (including Siamese networks and INNs), and graph-based methods for data fusion and map representation. These advancements are crucial for improving the reliability and scalability of robotic systems across various applications, from autonomous vehicles to indoor service robots and exploration missions. The development of energy-efficient, on-device solutions using neuromorphic computing is also a significant area of focus.