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docs: update VAD package path to e2e directory (#738)
* docs: update VAD package path to e2e directory
Update autoware_tensorrt_vad project link to reflect its migration from
planning/ to e2e/ directory in autoware_universe repository structure.
Signed-off-by: Max-Bin <vborisw@gmail.com>
* style(pre-commit): autofix
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Signed-off-by: Max-Bin <vborisw@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Copy file name to clipboardExpand all lines: docs/demos/digital-twin-demos/carla-tutorial.md
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@@ -18,7 +18,7 @@ It is integrated in autoware_universe and actively maintained to stay compatible
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TensorRT-optimized Vectorized Autonomous Driving ([VAD](https://github.com/hustvl/VAD)) node that replaces the traditional perception/localization/planning stack with a single end-to-end model trained on CARLA ([Bench2Drive](https://github.com/Thinklab-SJTU/Bench2Drive)). Ships with a CARLA-focused launch file and integrates with `autoware_launch` through `e2e_simulator.launch.xml`.
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- Project Link: [autoware_tensorrt_vad](https://github.com/autowarefoundation/autoware/tree/main/src/universe/autoware_universe/planning/autoware_tensorrt_vad) (README includes parameters, topics, and model details)
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- Project Link: [autoware_tensorrt_vad](https://github.com/autowarefoundation/autoware/tree/main/src/universe/autoware_universe/e2e/autoware_tensorrt_vad) (README includes parameters, topics, and model details)
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- Usage (CARLA E2E mode):
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1. Build the package and deps: `colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release --packages-up-to autoware_tensorrt_vad`.
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2. Prepare CARLA following `autoware_carla_interface` (use `carla_sensor_kit` so camera topics match the VAD training order: FRONT, BACK, FRONT_LEFT, BACK_LEFT, FRONT_RIGHT, BACK_RIGHT).
|**AFE-R760** (system, but the board AFE-R360 is also available) | Intel® Core™ Ultra 7/5 Processors | (Optional) MXM-type RTX A2000/A4500/5000Ada | <ul><li>4 GMSL2 cameras</li><li>Dual Channel DDR5-5600, up to 96GB</li><li>3 x LAN up to 2.5GbE</li><li>4 x RS-232/422/485</li><li>2 x USB-C & 2 USB-A (10Gbps)</li><li>2 x CAN-FD</li></ul> | <ul><li>Operating Temperature: -20 ~ 60° C with 0.7m/s air flow</li><li>Vibration During Operation: 3 Grms, IEC 60068-2-64, random, 5 ~ 500 Hz, 1 hr/axis.</li><li>Shock During Operation 30 G, IEC 60068-2-27, half sine, 11 ms duration</li><li>EMC: Heavy industrial certificates, CE/FCC Class B, UKCA, CCC, BSMI</li></ul> | Y |
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| Supported Products List | CPU | GPU | RAM, Interfaces | Environmental | Autoware Tested (Y/N) |
|**AFE-R760** (system, but the board AFE-R360 is also available) | Intel® Core™ Ultra 7/5 Processors | (Optional) MXM-type RTX A2000/A4500/5000Ada | <ul><li>4 GMSL2 cameras</li><li>Dual Channel DDR5-5600, up to 96GB</li><li>3 x LAN up to 2.5GbE</li><li>4 x RS-232/422/485</li><li>2 x USB-C & 2 USB-A (10Gbps)</li><li>2 x CAN-FD</li></ul> | <ul><li>Operating Temperature: -20 ~ 60° C with 0.7m/s air flow</li><li>Vibration During Operation: 3 Grms, IEC 60068-2-64, random, 5 ~ 500 Hz, 1 hr/axis.</li><li>Shock During Operation 30 G, IEC 60068-2-27, half sine, 11 ms duration</li><li>EMC: Heavy industrial certificates, CE/FCC Class B, UKCA, CCC, BSMI</li></ul> | Y |
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|**AFE-R750-X0A1U** (AGX Orin 32GB/64GB system, but the board ASR-A701 is also available) | 8/12-core NVIDIA Arm® Cortex A78AE v8.2 | 1792/2048-core NVIDIA Ampere GPU with 56/64 Tensor Cores | <ul><li>8 x GMSL2 cameras</li><li>BOSCH BMI088 IMU</li><li>Xsens MTi3 IMU (Optional)</li><li>32/64GB 256-bit LPDDR5 DRAM</li><li> 4 x 2.5GbE, 4 x USB 3.2 Type A, 2 x isolated CANFD, 16bit isolated DIO, 2 x RS232/422/485</li> </ul> | <ul><li>20~28V DC</li> <li>-10 ~ 60°C/50°C with 0.7 m/s air flow for 32GB/64GB</li></ul> | Y |
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Link to company website is [here.](https://campaign.advantech.online/en/AMR-Robotic-Solutions/)
@@ -21,13 +21,13 @@ ADLINK solutions which is used for autonomous driving and tested by one or more
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<!-- cspell: ignore Altra BLUEBOX Grms Quadro Vecow vecow -->
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| Supported Products List | CPU | GPU | RAM, Interfaces | Environmental | Autoware Tested (Y/N) |
| BLUEBOX 3.0 | 16 x Arm® Cortex®-A72 | Dual RTX 8000 or RTX A6000 | 16 GB RAM CAN, FlexRay, USB, Ethernet, DIO, SSD | ASIL-D | - |
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Link to company website is [here.](https://www.nxp.com/design/designs/bluebox-3-0-automotive-high-performance-compute-ahpc-development-platform:BlueBox)
@@ -49,8 +49,8 @@ Link to company website is [here.](https://www.nxp.com/design/designs/bluebox-3-
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Neousys solutions which is used for autonomous driving and tested by one or more community members are listed below:
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| Supported Products List | CPU | GPU| RAM, Interfaces | Environmental | Autoware Tested (Y/N) |
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