Robotics
TensorRT
ONNX
autoware
ros2
autonomous-driving
planning
end-to-end
e2e
trajectory-generation
camera
video
world-model
latent-world-model
v-jepa
jepa
latentdrive
Instructions to use AutowareFoundation/latent_drive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use AutowareFoundation/latent_drive with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Replace the lane change with a right turn in the scene replays
Browse files- README.md +3 -3
- SHA256SUMS +2 -2
- media/latent_drive_scenes.png +2 -2
- replay.mp4 +2 -2
README.md
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@@ -26,7 +26,7 @@ route and the ego motion into a 4 s ego trajectory, at 10 Hz. A V-JEPA ViT-L vid
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a small planning head reads the encoder's features together with the route and the ego state.
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<p align="center">
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<img src="media/latent_drive_scenes.png" width="100%" alt="Six scenes with the three-camera model's plan projected on the front camera: following a lane at 40 km/h,
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</p>
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Two models are published here, sharing the encoder, the route input and the output:
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@@ -55,7 +55,7 @@ Two models are published here, sharing the encoder, the route input and the outp
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| `camfront3-rptw-lane2-e1.onnx` | The three-camera model (1.25 GB) |
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| `camfront-rptw-lane2-e1.onnx` | The one-camera model (1.24 GB) |
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| `media/` | The scenes on this page |
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| `replay.mp4` | Open-loop replays of six scenes of
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| `deploy_metadata.yaml` | Deployment metadata recording the artifact version of this repository |
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| `SHA256SUMS` | Checksums of the files above |
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@@ -143,7 +143,7 @@ validation data and are not published.
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- **Known behaviours.** Where the route doubles back (a junction entry whose centerline turns back), near route
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points can land behind or beside the car and the plan cuts in; `autoware_latent_drive` drops route vertices
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that turn by more than 120°. The models creep slightly while the car is stopped.
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-
- **Evaluation.** The video preview and the scenes on this page are open-loop replays of
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(Tokyo, Ariake, 2026-10-23), made with `samples/rosbag/run_replay.sh`: the plan is drawn on the camera
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frames, not executed. The ribbon runs green (now) to red (+4 s).
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a small planning head reads the encoder's features together with the route and the ego state.
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<p align="center">
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| 29 |
+
<img src="media/latent_drive_scenes.png" width="100%" alt="Six scenes with the three-camera model's plan projected on the front camera: following a lane at 40 km/h, turning right at an intersection after yielding to oncoming traffic, a left turn at an intersection, starting on green and turning left, slowing down for a red light, and starting on green">
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</p>
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Two models are published here, sharing the encoder, the route input and the output:
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|
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| 55 |
| `camfront3-rptw-lane2-e1.onnx` | The three-camera model (1.25 GB) |
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| 56 |
| `camfront-rptw-lane2-e1.onnx` | The one-camera model (1.24 GB) |
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| `media/` | The scenes on this page |
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+
| `replay.mp4` | Open-loop replays of six scenes of two recorded drives, the three-camera model's plan drawn on the front camera; this page's video preview |
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| `deploy_metadata.yaml` | Deployment metadata recording the artifact version of this repository |
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| `SHA256SUMS` | Checksums of the files above |
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| 61 |
|
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| 143 |
- **Known behaviours.** Where the route doubles back (a junction entry whose centerline turns back), near route
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| 144 |
points can land behind or beside the car and the plan cuts in; `autoware_latent_drive` drops route vertices
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| 145 |
that turn by more than 120°. The models creep slightly while the car is stopped.
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| 146 |
+
- **Evaluation.** The video preview and the scenes on this page are open-loop replays of two recorded drives
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| 147 |
(Tokyo, Ariake, 2026-10-23), made with `samples/rosbag/run_replay.sh`: the plan is drawn on the camera
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| 148 |
frames, not executed. The ribbon runs green (now) to red (+4 s).
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| 149 |
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SHA256SUMS
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@@ -2,5 +2,5 @@
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8aa2f982fd0b07aac305d75a6522236c9b307ede7ca09223bb92381035c21659 camfront-rptw-lane2-e1.onnx
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6bd2eba88475af5e5a823eb39b6994e1c45a820049e73500f40a114dd0f3fb03 deploy_metadata.yaml
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c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 LICENSE
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-
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-
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8aa2f982fd0b07aac305d75a6522236c9b307ede7ca09223bb92381035c21659 camfront-rptw-lane2-e1.onnx
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6bd2eba88475af5e5a823eb39b6994e1c45a820049e73500f40a114dd0f3fb03 deploy_metadata.yaml
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c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4 LICENSE
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+
2dfcb26d20851b243d19aa689a15b371c13c655e7e86598197c9f19329772444 media/latent_drive_scenes.png
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b9bb481aa6084343cc43308dd192512834a36d3b4746084cd316a28e14fc9060 replay.mp4
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media/latent_drive_scenes.png
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Git LFS Details
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Git LFS Details
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:b9bb481aa6084343cc43308dd192512834a36d3b4746084cd316a28e14fc9060
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size 27499977
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