A python implemented error-state extended Kalman Filter. Suit for learning EKF and IMU integration.
Use simulated imu data (./data/imu_noise.txt) as input.
Output an trajectory estimated by esekf (./data/traj_esekf_out.txt) and a ground truth trajectory (./data/traj_gt_out.txt).
You can use evo to show both trajectories above.
evo_traj tum ./data/traj_esekf_out.txt --ref ./data/traj_gt_out.txt -p