US 12,217,515 B2
Training a codebook for trajectory determination
Ethan Miller Pronovost, Redwood City, CA (US)
Assigned to Zoox, Inc., Foster City, CA (US)
Filed by Zoox, Inc., Foster City, CA (US)
Filed on Jun. 30, 2022, as Appl. No. 17/855,696.
Prior Publication US 2024/0104934 A1, Mar. 28, 2024
Int. Cl. G06V 20/58 (2022.01); B60W 40/10 (2012.01)
CPC G06V 20/58 (2022.01) [B60W 40/10 (2013.01); B60W 2554/4049 (2020.02)] 20 Claims
OG exemplary drawing
 
6. A method comprising:
receiving, by a training component, state data representing a previous state of an object or a vehicle in an environment;
receiving, by the training component, feature vectors representing the vehicle and the object in the environment;
training a codebook to output a trained codebook, the training comprising:
assigning, based at least in part on the state data, a first token to represent the previous state of the object;
assigning a second token to represent a characteristic of the vehicle;
assigning a third token to represent a feature of the environment; and
mapping the feature vectors to respective tokens; and
outputting the trained codebook for use by a machine learned model configured to access tokens from the trained codebook and to arrange the first token, the second token, and the third token to represent a potential interaction between the vehicle and the object.