In this project, the structure of mapping and localization in an indoor environment is implemented using information from an IMU and range sensors. Information from IMU orientation and odometry information is integrated from a walking humanoid with a 2D laser range scanner (LIDAR) in order to build a 2D occupancy grid map of the walls and obstacles in the environment.
There are two sets of data: train & test, stored in "data" repository. Student are given only train data. There are totally 4 map corresponding to different dataset_id (0, ..., 3)
python main.py --split_name train --dataset_id <0, 1 or 2, or 3>
To generate figures, run
python gen_figures.py --split_name <train or test> --dataset_id <0, 1, or 2, 3>
Log file & images are all stored in "logs" repository