公开(公告)号：US11842530B2

公开(公告)日：2023-12-12

申请号：US17150995

申请日：2021-01-15

申请人： UATC, LLC

发明人： Sergio Casas ,  Cole Christian Gulino ,  Shun Da Suo ,  Katie Z. Luo ,  Renjie Liao ,  Raquel Urtasun

IPC分类号： G06V10/82 ,  B60W60/00 ,  G08G1/16 ,  G05D1/02 ,  G06V20/58 ,  G06F18/2137 ,  G06V30/19 ,  G06V30/24

CPC分类号： G06V10/82 ,  B60W60/0027 ,  G05D1/0212 ,  G06F18/2137 ,  G06V20/58 ,  G06V30/19173 ,  G08G1/166 ,  G06V30/2504

摘要： A computer-implemented method for determining scene-consistent motion forecasts from sensor data can include obtaining scene data including one or more actor features. The computer-implemented method can include providing the scene data to a latent prior model, the latent prior model configured to generate scene latent data in response to receipt of scene data, the scene latent data including one or more latent variables. The computer-implemented method can include obtaining the scene latent data from the latent prior model. The computer-implemented method can include sampling latent sample data from the scene latent data. The computer-implemented method can include providing the latent sample data to a decoder model, the decoder model configured to decode the latent sample data into a motion forecast including one or more predicted trajectories of the one or more actor features. The computer-implemented method can include receiving the motion forecast including one or more predicted trajectories of the one or more actor features from the decoder model.

公开(公告)号：US20240096083A1

公开(公告)日：2024-03-21

申请号：US18519976

申请日：2023-11-27

申请人： UATC, LLC

发明人： Sergio Casas ,  Cole Christian Gulino ,  Shun Da Suo ,  Katie Z. Luo ,  Renjie Liao ,  Raquel Urtasun

IPC分类号： G06V10/82 ,  B60W60/00 ,  G05D1/02 ,  G06F18/2137 ,  G06V20/58 ,  G06V30/19 ,  G08G1/16

CPC分类号： G06V10/82 ,  B60W60/0027 ,  G05D1/0212 ,  G06F18/2137 ,  G06V20/58 ,  G06V30/19173 ,  G08G1/166 ,  G06V30/2504

摘要： A computer-implemented method for determining scene-consistent motion forecasts from sensor data can include obtaining scene data including one or more actor features. The computer-implemented method can include providing the scene data to a latent prior model, the latent prior model configured to generate scene latent data in response to receipt of scene data, the scene latent data including one or more latent variables. The computer-implemented method can include obtaining the scene latent data from the latent prior model. The computer-implemented method can include sampling latent sample data from the scene latent data. The computer-implemented method can include providing the latent sample data to a decoder model, the decoder model configured to decode the latent sample data into a motion forecast including one or more predicted trajectories of the one or more actor features. The computer-implemented method can include receiving the motion forecast including one or more predicted trajectories of the one or more actor features from the decoder model.