# US 10,481,267 B2 · Undistorted raw LiDAR scans and static point extractions method for ground truth static scene sparse flow generation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,481,267 B2 - Document ID: US10481267B2 - Status: Granted - Kind: B2 - Application number: 15/621,918 - Filed: 2017-06-13 - Published: 2018-12-13 - Granted: 2019-11-19 - Earliest claimed: 2017-06-13 - Assignees: Tusimple, Inc. - Applicants: Tusimple - Inventors: Yi Wang; Yi Luo; Wentao Zhu; Panqu Wang - Web page: https://patentgrep.com/patent/US10481267B2 ## CPC - G01S 17/89: for mapping or imaging - G01S 7/4808: {Evaluating distance, position or velocity data} - G01S 17/86: Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders - G01S 17/931: of land vehicles - G05D 1/00: Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots (drive control systems specially adapted for autonomous road vehicles B60W60/00) - G05D 1/0231: {using optical position detecting means (position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16)} - G05D 1/0278: {using satellite positioning signals, e.g. GPS} - G06T 7/33: using feature-based methods - B60W 2420/408: Radar; Laser, e.g. lidar - G06T 2207/10028: Range image; Depth image; 3D point clouds - G06T 2207/30252: Vehicle exterior; Vicinity of vehicle - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT ## Abstract A method of generating a ground truth dataset for motion planning of a vehicle is disclosed. The method includes: obtaining undistorted LiDAR scans; identifying, for a pair of undistorted LiDAR scans, points belonging to a static object in an environment; aligning the close points based on pose estimates; and transforming a reference scan that is close in time to a target undistorted LiDAR scan so as to align the reference scan with the target undistorted LiDAR scan. ## Claims ### Claim 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: transforming LiDAR scans into undistorted LiDAR scans based on LiDAR's poses for the motion planning of a vehicle; identifying, for a pair of undistorted LiDAR scans, points belonging to a static object in an environment; aligning the close points based on pose estimates; and transforming a reference scan that is close in time to a target undistorted LiDAR scan so as to align the reference scan with the target undistorted LiDAR scan. ### Claim 2 (depends on 1) The method according to claim 1 further comprising: determining that a distance between a point in the target undistorted LiDAR scan and its closest point in the aligned reference scan is smaller than a threshold. ### Claim 3 (depends on 2) The method according to claim 2 further comprising: extracting the point from the target undistorted LiDAR scan. ### Claim 4 (depends on 3) The method according to claim 3 further comprising: generating a LiDAR static-scene point cloud based on undistorted LiDAR scans. ### Claim 5 (depends on 1) The method according to claim 1, further comprising: collecting LiDAR scans. ### Claim 6 (depends on 5) The method according to claim 5 further comprising: collecting LiDAR scans in the form of a swing while observing points within the swing at different time points. ### Claim 7 (depends on 6) The method according to claim 6, wherein collecting the LiDAR scans further comprising: collecting the LiDAR scans in the form of a swing in 20 Hz. ### Claim 8 (depends on 5) The method according to claim 5 further comprising: detecting two pose estimates that are closest to LiDAR scan acquisition time. ### Claim 9 (depends on 8) The method according to claim 8, wherein the pose estimates include GNSS-inertial pose estimates. ### Claim 10 (depends on 8) The method according to claim 8 further comprising: determining LiDAR's poses based on interpolation. ### Claim 11 (depends on 10) The method according to claim 10, wherein the interpolation includes a linear interpolation. ### Claim 12 A system for generating a ground truth dataset for motion planning, the system comprising: an internet server, comprising: an I/O port, configured to transmit and receive electrical signals to and from a client device; a memory; one or more processing units; and one or more programs stored in the memory and configured for execution by the one or more processing units, the one or more programs including instructions for: a collecting module configured to collect LiDAR scans for the motion planning of a vehicle; a detecting module configured to detect two pose estimates that are closest to LiDAR scan accusation time; a determining module configured to determine LiDAR's poses by interpolating the two pose estimates; and a transforming module configured to transform the LiDAR scans into undistorted LiDAR scans based on the LiDAR's poses. ### Claim 13 (depends on 12) The system according to claim 12, wherein the collecting module is configured to collect LiDAR scans in the form of a swing while observing points within the swing at different time points. ### Claim 14 (depends on 13) The system according to claim 13, wherein the collecting module is configured to collect LiDAR scans in the form of a swing in 20 Hz. ### Claim 15 (depends on 12) The system according to claim 12, wherein the pose estimates include GNSS-inertial pose estimates. ### Claim 16 (depends on 12) The system according to claim 12, wherein the interpolation includes a linear interpolation. ### Claim 17 A system having a non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions which, when executed by the one or more processors of a computing device, cause the computing device to: collect LiDAR scans for a motion planning of a vehicle; detect two pose estimates that are closest to LiDAR scan accusation time; determine LiDAR's poses by interpolating the two pose estimates; and transform the LiDAR scans into undistorted LiDAR scans based on the LiDAR's poses. ### Claim 18 (depends on 17) The system according to claim 17, further comprising instructions which, when executed by the one or more processors, cause the computing device to: identify, for a pair of undistorted LiDAR scans, points belonging to a static object in an environment. ### Claim 19 (depends on 18) The system according to claim 18, further comprising instructions which, when executed by the one or more processors, cause the computing device to: align the close points based on GNSS-inertial estimates. ### Claim 20 (depends on 19) The system according to claim 19, further comprising instructions which, when executed by the one or more processors, cause the computing device to: transform a reference scan that is close in time to a target undistorted LiDAR scan so as to align the reference scan with the target undistorted LiDAR scan. ### Claim 21 (depends on 20) The system according to claim 20, further comprising instructions which, when executed by the one or more processors, cause the computing device to: determine that a distance between a point in the target undistorted LiDAR scan and its closest point in the aligned reference scan is smaller than a threshold. ### Claim 22 (depends on 21) The system according to claim 21, further comprising instructions which, when executed by the one or more processors, cause the computing device to: extract the point from the target undistorted LiDAR scan. ### Claim 23 (depends on 22) The system according to claim 22, further comprising instructions which, when executed by the one or more processors, cause the computing device to: generate a LiDAR static-scene point cloud based on undistorted LiDAR scans. ### Claim 24 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: collecting LiDAR scans for the motion planning of a vehicle; detecting two pose estimates that are closest to LiDAR scan accusation time; determining LiDAR's poses by linearly interpolating the two GNSS-inertial pose estimates that are closest to LiDAR scan accusation time; and transforming the LiDAR scans into undistorted LiDAR scans based on the LiDAR's poses. ### Claim 25 (depends on 24) The method according to claim 24, wherein collecting LiDAR scans further comprises: collecting the LiDAR scans in the form of a swing while observing points within the swing at different time points. ### Claim 26 (depends on 25) The method according to claim 25 further comprising: collecting LiDAR scans in the form of a swing in 20 Hz. ### Claim 27 (depends on 24) The method according to claim 24, wherein the interpolation includes a linear interpolation. ### Claim 28 (depends on 24) The method according to claim 24, further comprising: identifying, for a pair of undistorted LiDAR scans, points belonging to a static object in an environment. ### Claim 29 (depends on 28) The method according to claim 28, further comprising: aligning close points based on GNSS-inertial estimates. ### Claim 30 (depends on 29) The method according to claim 29, further comprising: transforming a reference scan that is close in time to a target undistorted LiDAR scan so as to align the reference scan with the target undistorted LiDAR scan. ### Claim 31 (depends on 30) The method according to claim 30, further comprising: determining that a distance between a point in the target undistorted LiDAR scan and its closest point in the aligned reference scan is smaller than a threshold. ### Claim 32 (depends on 31) The method according to claim 31, further comprising: extracting the point from the target undistorted LiDAR scan. ### Claim 33 (depends on 32) The method according to claim 32, further comprising: generating a LiDAR static-scene point cloud based on the undistorted LiDAR scans.