Method and system for vehicle odometry using coherent range doppler optical sensors
A system and method for vehicle odometry using coherent range Doppler optical sensors. The system and method includes operating a Doppler light detection and ranging (LIDAR) system to collect raw point cloud data that indicates for a point a plurality of dimensions, wherein a dimension of the plurality of dimensions includes an inclination angle, an azimuthal angle, a range, or a relative speed between the point and the LIDAR system; determining a corrected velocity vector for the Doppler LIDAR system based on the raw point cloud data; and producing revised point cloud data that is corrected for the velocity of the Doppler LIDAR system.
1. A method comprising:
collecting, by a light detection and ranging (LIDAR) system of a vehicle, point cloud data;
producing, by the LIDAR system based on the point cloud data, a velocity vector for the vehicle;
determining, by the LIDAR system, whether a scan by the LIDAR system is unidirectional or bidirectional;
in response to determining that the scan is bidirectional, revising, by the LIDAR system, the velocity vector and the point cloud data based on an average velocity in a scan direction; and
in response to determining that the scan is unidirectional, revising, by the LIDAR system, the velocity vector and the point cloud data based on a discontinuity in velocity measurements.
2. The method as recited in claim 1 , wherein the revising the velocity vector and the point cloud data based on an average velocity in a scan direction comprises:
calculating a translational velocity for each scan direction; and
averaging the calculated translational velocities.
3. The method as recited in claim 2 , wherein the translational velocities are averaged across evenly balanced opposing-direction scans such that an erroneous transverse velocity is canceled out.
4. The method as recited in claim 1 , wherein the revising the velocity vector and the point cloud data based on a discontinuity in velocity measurements comprises:
detecting the discontinuity in the velocity measurements at a limit of a field of view (FOV) of a sensor; and
detecting a transverse velocity at a time of the discontinuity.
5. The method as recited in claim 4 , wherein the time of the discontinuity is when a beam wraps around to a far side of the FOV of the sensor.
6. The method as recited in claim 1 , wherein the point cloud data comprises data representing at least one of an inclination angle, an azimuthal angle, a range, or a speed.
7. The method as recited in claim 1 , wherein the velocity vector is a translation velocity vector.
8. A non-transitory computer-readable storage medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising causing a light detection and ranging (LIDAR) system of a vehicle to:
collect point cloud data;
produce, based on the point cloud data, a velocity vector for the vehicle;
determine whether a scan by the LIDAR system is unidirectional or bidirectional;
in response to determining that the scan is bidirectional, revise the velocity vector and the point cloud data based on an average velocity in a scan direction; and
in response to determining that the scan is unidirectional, revise the velocity vector and the point cloud data based on a discontinuity in velocity measurements.
9. The non-transitory computer-readable medium as recited in claim 8 , wherein in revising the velocity vector and the point cloud data based on an average velocity in a scan direction, the instructions cause the LIDAR system to:
calculate a translational velocity for each scan direction; and
average the calculated translational velocities.
10. The non-transitory computer-readable medium as recited in claim 9 , wherein the translational velocities are averaged across evenly balanced opposing-direction scans such that an erroneous transverse velocity is canceled out.
11. The non-transitory computer-readable medium as recited in claim 8 , wherein in revising the velocity vector and the point cloud data based on a discontinuity in velocity measurements, the instructions cause the LIDAR system to:
detect the discontinuity in the velocity measurements at a limit of a field of view (FOV) of a sensor; and
detect a transverse velocity at a time of the discontinuity.
12. The non-transitory computer-readable medium as recited in claim 11 , wherein the time of the discontinuity is when a beam wraps around to a far side of the FOV of the sensor.
13. The non-transitory computer-readable medium as recited in claim 8 , wherein the point cloud data comprises data representing at least one of an inclination angle, an azimuthal angle, a range, or a speed.
14. The non-transitory computer-readable medium as recited in claim 8 , wherein the velocity vector is a translation velocity vector.
15. A light detection and ranging (LIDAR) system comprising:
one or more processors configured to:
collect point cloud data;
produce, based on the point cloud data, a velocity vector for the vehicle;
determine whether a scan by the LIDAR system is unidirectional or bidirectional;
in response to determining that the scan is bidirectional, revise the velocity vector and the point cloud data based on an average velocity in a scan direction; and
in response to determining that the scan is unidirectional, revise the velocity vector and the point cloud data based on a discontinuity in velocity measurements.
16. The system as recited in claim 15 , wherein in revising the velocity vector and the point cloud data based on an average velocity in a scan direction, the one or more processors are configured to:
calculate a translational velocity for each scan direction; and
average the calculated translational velocities.
17. The system as recited in claim 16 , wherein the translational velocities are averaged across evenly balanced opposing-direction scans such that an erroneous transverse velocity is canceled out.
18. The system as recited in claim 15 , wherein in revising the velocity vector and the point cloud data based on a discontinuity in velocity measurements, the one or more processors are configured to:
detect the discontinuity in the velocity measurements at a limit of a field of view (FOV) of a sensor; and
detect a transverse velocity at a time of the discontinuity.
19. The system as recited in claim 18 , wherein the time of the discontinuity is when a beam wraps around to a far side of the FOV of the sensor.
20. The system as recited in claim 15 , wherein the velocity vector is a translation velocity vector.