Online object-level bias estimation for multi-sensor fusion

A system comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, configure the system to:
• receive, from a first sensor, a first set of object data associated with a location of an object in a three-dimensional space, wherein the first sensor is associated with a first bias;
• receive, from a second sensor, a second set of object data associated with the location of the object in the three-dimensional space, wherein the second sensor is associated with a second bias;
• predict, using a trained machine-learning model, a combined bias, wherein the trained machine-learning model is trained using historical sets of object data and historical biases to estimate a position of one or more objects in the three-dimensional space;
• and
• generate a calibrated location of the object based on the combined bias using the trained machine-learning model.

A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:

• receive, from a first sensor, a first set of object data associated with a location of an object in a three-dimensional space, wherein the first sensor is associated with a first bias;
• receive, from a second sensor, a second set of object data associated with the location of the object in the three-dimensional space, wherein the second sensor is associated with a second bias;
• predict, using a trained machine-learning model, a combined bias, wherein the trained machine-learning model is trained using historical sets of object data and historical biases to estimate a position of one or more objects in the three-dimensional space;
• and
• generate a calibrated location of the object based on the combined bias using the trained machine-learning model.