US 2026/0311342 A1Published application

System and method for calibrating 3d sensor coordinate based on scene flow network

AssigneesHyundai Motor Company, Kia Corporation

InventorsHyeon Jun LIM, Dong Wook SHU, Ju Heon BAEG, Su Rin JO

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Abstract

A system and a method for recognizing an object by an artificial intelligence (AI) module and an autonomous driving sensor are disclosed. The AI module performs a first step for training and executing the scene flow network, which outputs a scene flow, in real time based on input data from the autonomous driving sensor, a second step for performing motion segmentation with respect to points including a static object or a dynamic object present under the surrounding environment, a third step for extracting a representative static object vector by applying a particle filter to the input data, which is temporally and spatially accumulated, from the autonomous driving sensor, and a fourth step for calibrating coordinates of the autonomous driving sensor, using at least one of a roll value, a pitch value, a yaw value, or a z value of the representative static object vector.

Claims20

Dependent claims

An apparatus of a vehicle, the apparatus comprising:

a sensor configured to obtain a plurality of pieces of point data associated with at least one object in a surrounding environment of the vehicle;
a memory configured to store the plurality of pieces of point data;
and
a processor circuit configured to:
based on the plurality of pieces of point data, train and execute an artificial intelligence (AI) model to output a scene flow in real time, wherein the scene flow is associated with motion vectors each representing a movement of a point in the plurality of pieces of point data between two consecutive time points,
perform motion segmentation on the plurality of pieces of point data, wherein at least part of the plurality of pieces of point data is associated with a static object or a dynamic object present in the surrounding environment,
extract a representative static object vector by applying a particle filter to the plurality of pieces of point data, wherein the plurality of pieces of point data is accumulated from different positions of the sensor at different time points from the sensor, and
adjust coordinates of the sensor, using at least one of:
a roll value of the representative static object vector,
a pitch value of the representative static object vector,
a yaw value of the representative static object vector, or
a height value of the representative static object vector.

9 more elements

A method performed by an apparatus of a vehicle, the method comprising:

obtaining, via a sensor of the vehicle, a plurality of pieces of point data associated with at least one object in a surrounding environment of the vehicle;
based on the plurality of pieces of point data, training and executing an artificial intelligence (AI) model to output a scene flow in real time, wherein the scene flow associated with motion vectors each representing a movement of a point in the plurality of pieces of point data between two time points;
performing motion segmentation on the plurality of pieces of point data, wherein at least part of the plurality of pieces of point data is associated with a static object or a dynamic object present in the surrounding environment;
extracting a representative static object vector by applying a particle filter to the plurality of pieces of point data, wherein the plurality of pieces of point data are temporally and spatially accumulated from the sensor;
and
adjusting coordinates of the sensor, using at least one of:
a roll value of the representative static object vector,
a pitch value of the representative static object vector,
a yaw value of the representative static object vector, or
a height value of the representative static object vector.

7 more elements

A vehicle comprising:

a sensor;
a driving control circuit configured to control autonomous driving of the vehicle;
and
a processor circuit configured to:
obtain point cloud data at different time points from the sensor,
identify a plurality of static objects based on the point cloud data,
compare positional changes of the plurality of static objects between the different time points,
determine, based on the comparison of the positional changes, a misalignment between coordinates of the sensor and coordinates of the vehicle,
output, based on the misalignment, a signal indicating calibration parameters, wherein the calibration parameters comprise at least one of a roll value, a pitch value, a yaw value, or a height value,
adjust, based on the signal, the coordinates of the sensor such that the coordinates of the sensor are aligned with the coordinates of the vehicle, and
control, via the driving control circuit and based on the adjusted coordinates of the sensor, autonomous driving of the vehicle.

8 more elements

Dependencies are inferred from the claim text.