US 2026/0208762 A1 · Generating a Trajectory for an Autonomous Vehicle

Abstract

Systems and methods for generating a trajectory for an autonomous vehicle, AV, using an autonomy stack are disclosed. The autonomy stack can include a first component for generating a AV trajectory based on sensor inputs and a second component for adjusting the trajectory based on the sensor inputs. Both the first and second components can each include a perception module and a planning module. The method can include: identifying, using a perception module of a first component, objects based on sensor inputs; generating, using a planning module of the first component, a trajectory for the AV based on the objects identified by the perception module of the first component; identifying, using a perception module of a second component, objects based on the sensor inputs; and adjusting, using a planning module of the second component, the trajectory based on the objects identified by the perception module of the second component.

Claims18

Dependent claims

A computer-implemented method of generating a trajectory for an autonomous vehicle, AV, using an autonomy stack, the autonomy stack including a first component and a second component, the first component for generating a trajectory for the AV based on sensor inputs and the second component for adjusting the trajectory based on the sensor inputs, the first and second components each including a perception module and a planning module, the computer-implemented method comprising:

identifying, using the perception module of the first component, objects based on sensor inputs;
generating, using the planning module of the first component, a trajectory for the AV based on the objects identified by the perception module of the first component;
identifying, using a perception module of the second component, objects based on the sensor inputs;
and
adjusting, using the planning module of the second component, the trajectory based on the objects identified by the perception module of the second component,
wherein the perception module of the second component includes one or more rules-based models and one or more machine learning models.

3 more elements

A computer-implemented method of training a machine learning algorithm of a perception module of a second component in an autonomy stack for controlling an autonomous vehicle, AV, to identify objects from sensor inputs, the autonomy stack including a first component and the second component, the first component for generating a trajectory for the AV based on sensor inputs and the second component for adjusting the trajectory based on the sensor inputs, the first component including a perception module and a planning module, and the second component including the perception module and a planning module, wherein the perception module of the second component includes one or more rules-based models and one or more machine learning models the computer-implemented method comprising:

identifying, using the one or more rules-based models, objects using sensor inputs;
labelling the sensor inputs and the identified objects automatically as paired data;
and
training the one or more machine learning models to identify objects using the paired sensor inputs and identified objects.

1 more element

Dependencies are inferred from the claim text.

Generating a Trajectory for an Autonomous Vehicle

Life of this patent

Generating a Trajectory for an Autonomous Vehicle

Life of this patent

Abstract

Claims18