Methods and systems for predicting a trajectory of an object
AssigneeAptiv Technologies AG
InventorsDominic Spata, Arne Grumpe, Mirko Meuter, Ido Freeman
Life of this patent
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Abstract
A computer implemented method for predicting a trajectory of an object comprises the following steps carried out by computer hardware components: acquiring radar data of the object; determining first intermediate data based on the radar data based on a residual backbone using a recurrent component; determining second intermediate data based on the first intermediate data using a feature pyramid; and predicting the trajectory of the object based on the second intermediate data.
Claims23
A method comprising:
- acquiring, by computer hardware components, a plurality of frames of radar data of an object;
- via a convolutional neural network, performing temporal fusion of features of the plurality of frames of radar data, wherein the convolutional neural network comprises a residual backbone, a feature pyramid and a regression head;
- determining, using a recurrent component, first intermediate data based on the plurality of frames of radar data and the residual backbone;
- determining, using the feature pyramid, second intermediate data based on the first intermediate data, wherein the second intermediate data comprises a plurality of features;
- determining via the regression head a plurality of coefficients to time-continuous polynomial functions based on the plurality of features;
- and
- predicting, based on the plurality of coefficients, a trajectory of the object.
A system, the system comprising a plurality of computer hardware components configured to:
- acquire a plurality of frames of radar data of an object;
- via a convolutional neural network of the plurality of computer hardware components, perform temporal fusion of features of the plurality of frames of radar data, wherein the convolutional neural network comprises a residual backbone, a feature pyramid and a regression head;
- determine, using a recurrent component, first intermediate data based on the plurality of frames of radar data based on the residual backbone;
- determine, using the feature pyramid, second intermediate data based on the first intermediate data, wherein the second intermediate data comprises a plurality of features;
- determine via the regression head a plurality of coefficients to time-continuous polynomial functions based on the plurality of features;
- and
- predict, based on the plurality of coefficients, a trajectory of the object.
A non-transitory computer readable medium comprising instructions, that when executed, configure at least one processor to:
- acquire a plurality of frames of radar data of an object;
- via a convolutional neural network, perform temporal fusion of features of the plurality of frames of radar data, wherein the convolutional neural network comprises a residual backbone, a feature pyramid and a regression head;
- determine, using a recurrent component, first intermediate data based on the plurality of frames of radar data based on the residual backbone;
- determine, using the feature pyramid, second intermediate data based on the first intermediate data, wherein the second intermediate data comprises a plurality of features;
- determine via the regression head a plurality of coefficients to time-continuous polynomial functions based on the plurality of features;
- and
- predict, based on the plurality of coefficients, a trajectory of the object.
Dependencies are inferred from the claim text.