Sensor calibration and time method for ground truth static scene sparse flow generation

1. A method of generating a ground truth dataset for motion planning for a non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, causes the computing device to perform the following steps comprising:

performing data alignment for a set of sensors by calibrating the sensors in a common coordinate system and providing time synchronization for data acquired among the sensors;

collecting data in an environment, using the sensors;

calculating light detecting and ranging (LiDAR)'s poses using the collected data;

stitching multiple LiDAR scans to form a local map;

refining positions of close points of static objects in the local map based on a matching algorithm, wherein the close points are aligned based on global navigation satellite system (GNSS)-inertial estimates; and

projecting 3D points in the local map onto corresponding images.

2. The method according to claim 1 , wherein performing data alignment comprises:

calibrating intrinsic parameters of each beam using a supervised method before calibrating transformation between an inertial navigation system and a LiDAR coordinate.

3. The method according to claim 2 , wherein the inertial navigation system includes a global navigation satellite system (GNSS)-inertial measurement unit (IMU).

4. The method according to claim 1 , wherein performing data alignment comprises:

collecting LiDAR scans in the form of a sweep; and

correcting motion distortion within the sweep.

5. The method according to claim 1 , wherein performing data alignment comprises:

calibrating a set of cameras by multiple shots; and

calibrating transformation between the LiDAR and the camera coordinate.

6. The method according to claim 1 , wherein performing data alignment comprises:

synchronizing data acquisition of a camera and the LiDAR by a trigger metric.

7. The method according to claim 1 , wherein estimating LiDAR's poses comprises:

interpolating relative positions from a GNSS-inertial system.

8. The method according to claim 1 , wherein projecting 3D points is based on refined position estimates and a calibrated extrinsic transformation between sensors.

9. A system, comprising one or more processors and one or more programs including instructions which, when executed by the one or more processors, cause the system to:

perform data alignment for a set of sensors by calibrating the sensors in a common coordinate system and providing time synchronization for data acquired among the sensors;

calculate light detecting and ranging (LiDAR)'s poses based on data collected by the sensors;

stitch multiple LiDAR scans to form a local map;

refine positions of close points of static objects in the local map based on a matching algorithm, wherein the close points are aligned based on global navigation satellite system (GNSS)-inertial estimates; and

project 3D points in the local map onto corresponding images.

10. The system according to claim 9 , further comprising instructions which, when executed by the one or more processors, cause the system to:

calibrate intrinsic parameters of each beam using a supervised method before calibrate transformation between an inertial navigation system and a LiDAR coordinate.

11. The system according to claim 10 , wherein the inertial navigation system includes a global navigation satellite system (GNSS)-inertial measurement unit (IMU).

12. The system according to claim 9 , further comprising instructions which, when executed by the one or more processors, cause the system to:

calibrate a set of cameras by multiple shots; and

calibrate transformation between the LiDAR and the camera coordinate.

13. The system according to claim 9 , further comprising instructions which, when executed by the one or more processors, cause the system to:

synchronize data acquisition of a camera and the LiDAR by a trigger metric.

14. The system according to claim 9 , further comprising instructions which, when executed by the one or more processors, cause the system to:

interpolate relative positions from a GNSS-inertial system.

15. The system according to claim 9 , further comprising instructions which, when executed by the one or more processors, cause the system to:

project 3D points based on refined position estimates and a calibrated extrinsic transformation between sensors.