diegoavillegasg IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation issues

diegoavillegasg / IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation

State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).

190 stars 37 forks source link

issues

Newest

Newest Most commented Recently updated Oldest Least commented Least recently updated

I want to evalute the accuracy of estimated value and the ground truth,but i am surprised to find that the two dimensions(ground truth is 8734, estimate is 10918) is are different,why?

#4 miaozujia opened 2 years ago
0
paper about this code

#3 liangsongLee closed 4 years ago
0
How to integrate this module with real system.

#2 ajay1606 opened 4 years ago
4
Help needed to test the package

#1 ajay1606 closed 4 years ago
0

diegoavillegasg / IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation

issues

I want to evalute the accuracy of estimated value and the ground truth,but i am surprised to find that the two dimensions(ground truth is 8734, estimate is 10918) is are different,why?

paper about this code

How to integrate this module with real system.

Help needed to test the package