Indoor Mobile Robot

Indoor mobile robot research focuses on enabling robots to navigate and perform tasks effectively within complex indoor environments. Current efforts concentrate on improving robot localization and mapping accuracy using sensor fusion techniques (combining LiDAR, IMU, cameras, and WiFi), advanced algorithms like SLAM and meta-learning for depth estimation, and robust occupancy grid prediction methods to handle dynamic obstacles. These advancements are crucial for enhancing the safety and reliability of autonomous indoor robots, with applications ranging from assistive robotics for the visually impaired to autonomous delivery and service robots in various settings.