SYSTEMS AND METHODS FOR A FIRST AUTONOMOUS VEHICLE TO IDENTIFY AND UTILIZE A UNIQUE LIDAR PROJECTED PATTERN OF A SECOND AUTONOMOUS VEHICLE

1 . A method for a first vehicle to detect and identify a second vehicle using a LIDAR pattern projected by the second vehicle, the system comprising:

detecting, by a processing device of a first vehicle and utilizing at least one position detecting mechanism, a current position of the first vehicle at a first point in time, thereby determining self-position data for first vehicle at the first point in time;

detecting, at the first point in time and via at least one sensor in communication with the processing device, the sensor being operable to detect a light detection and ranging (LIDAR) pattern projected onto a surface of an environment by a LIDAR device of a second vehicle being followed by the first vehicle, data descriptive of the LIDAR pattern being projected by the LIDAR device of the second vehicle as the second vehicle travels along a route through an environment;

matching, utilizing LIDAR pattern data stored in a non-transitory memory device in communication with the processing device, the LIDAR pattern data to one of a plurality of unique LIDAR patterns described by the LIDAR pattern data; and

inferring, by the processing device and based on the matching, identification data defining the LIDAR device that is projecting the LIDAR pattern, thereby inferring identification data for the second vehicle.

2 . The method of claim 1 , further comprising:

determining, using at least one of (i) the LIDAR pattern, (ii) the self-position data and (iii) the identification data for the second vehicle, at least one of an orientation, a location and a position of the second vehicle at the first point in time.

3 . The method of claim 2 , further comprising:

determining, at a second point in time, a second position of the second vehicle;

determining a change in the position of the second vehicle over time; and

generating a map, based on the change in the position, of the route the second vehicle is traversing through the environment.

4 . The method of claim 1 , wherein the identification data defining the LIDAR device that is projecting the LIDAR pattern comprises data defining at least one of a make and model of the LIDAR device.

5 . The method of claim 1 , wherein the identification data defining the LIDAR device that is projecting the LIDAR pattern comprises data defining a particular unit of the LIDAR device.

6 . The method of claim 1 , wherein the data descriptive of the LIDAR pattern comprises LIDAR point clouds emitted by the LIDAR device of the second vehicle as reflected on the environment, further comprising:

generating a 3-D map of the environment using the LIDAR point clouds.

7 . The method of claim 6 , wherein the 3-D map is generated using the data descriptive of the LIDAR pattern of the second vehicle and additional data comprising at least one additional LIDAR pattern of at least one additional vehicle followed by the first vehicle.

8 . The method of claim 6 , wherein the generating of the 3-D map comprises:

utilizing the LIDAR pattern to generate the 3-D map; and

determining empty areas of the 3-D map to be areas that fill a gap between the self-position data and a point perceived in the environment.

9 . The method of claim 1 , wherein the at least one sensor comprises a plurality of sensors, further comprising:

triangulating each point of the LIDAR pattern being projected by the LADAR device of the second vehicle.

10 . The method of claim 1 , wherein the first vehicle is an aerial vehicle comprising at least one of a drone, airship, airplane or satellite.

11 . The method of claim 1 , wherein the second vehicle is a ground vehicle.

12 . The method of claim 1 , further comprising:

determining a pose difference between the first vehicle and second vehicle.

13 . The method of claim 12 , wherein the first vehicle is a drone and wherein the pose difference is utilized by the processing device to estimate at least one of a location and speed of the second vehicle.

14 . The method of claim 1 , further comprising:

detecting a change in the LIDAR pattern being projected by the LIDAR device of the second vehicle; and

decrypting a communication from the second vehicle based on the change in the LIDAR pattern.

15 . The method of claim 1 , further comprising:

detecting, via the at least one sensor, a second LIDAR pattern being projected by the LIDAR device of the second vehicle as it travels along the route through the environment; and

matching, using the LIDAR pattern data, the second LIDAR pattern to one of the plurality of unique LIDAR patterns.

16 . The method of claim 1 , further comprising:

approximating a speed of the second vehicle using at least one of (i) a “center of mass” of points illuminated via the LIDAR pattern; (ii) a “center of mass” of areas that are densely illuminated via the LIDAR pattern; and (iii) a “center of mass” of areas that are determined by the first vehicle to be flat.

17 . The method of claim 1 , wherein the processing device is operable to determine elevation data for the environment utilizing one of: (i) elevation data for the environment as stored in the memory device; (ii) elevation data for the environment as stored in a remote database accessible to the processing device; (iii) additional data sensed by the sensor; and (iv) flat earth assumptions.

18 . The method of claim 1 , wherein the data descriptive of the LIDAR pattern comprises data defining illumination of a road the second vehicle is traversing as well as data defining illumination of areas of the environment outside of the road, further comprising:

redacting from the data descriptive of the LIDAR pattern, the data defining illumination of areas of the environment outside of the road, and utilizing the data defining illumination of the road the second vehicle is traversing.

19 . The method of claim 1 , wherein the second vehicle comprises a fixed facility.

20 . The method of claim 1 , wherein the first vehicle and the second vehicle each comprises a vehicle in a convoy of vehicles, the first vehicle being positioned behind the second vehicle in said convoy, and wherein the second vehicle includes at least one second sensor operable to determine whether the first vehicle is following the second vehicle.