[clean] Correct release documentation

README.md

@@ -3,7 +3,7 @@
 ![Demo](examples/assets/tutorial_multicamera_edex.gif)
 
 
-### [ArXiv paper](https://www.arxiv.org/abs/2506.04359) | [Python API](https://nvidia-isaac.github.io/cuVSLAM/python/) | [C++ API](https://nvidia-isaac.github.io/cuVSLAM/cpp/) | [ROS2](https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_visual_slam)
+### [Latest release](https://github.com/nvidia-isaac/cuVSLAM/releases/latest) | [ArXiv paper](https://www.arxiv.org/abs/2506.04359) | [Python API](https://nvidia-isaac.github.io/cuVSLAM/python/) | [C++ API](https://nvidia-isaac.github.io/cuVSLAM/cpp/) | [ROS2](https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_visual_slam)
 
 ## Overview
 
@@ -73,6 +73,9 @@ To use cuVSLAM in a ROS2 environment:
 - [cuVSLAM Technical Report](https://www.arxiv.org/abs/2506.04359)
 - [PyCuVSLAM API Documentation](https://nvidia-isaac.github.io/cuVSLAM/python/)
 - [cuVSLAM C++ API Documentation](https://nvidia-isaac.github.io/cuVSLAM/cpp/)
+- Version-matched offline API documentation is available as `cuvslam-docs-<version>.tar.gz` on the
+  [latest release](https://github.com/nvidia-isaac/cuVSLAM/releases/latest). Extract it and open
+  `python/index.html` or `cpp/index.html`.
 
 # Performance
 
@@ -107,19 +110,27 @@ PyCuVSLAM is the Python wrapper (bindings) for the cuVSLAM library.
 Pre-built wheels are available on the [cuVSLAM releases page](https://github.com/nvidia-isaac/cuVSLAM/releases)
 for the following configurations:
 
-| Ubuntu | Python | CUDA | Architectures |
-|--------|--------|------|---------------|
-| 22.04 | 3.10 | 12, 13 | x86_64, aarch64 |
-| 24.04+ | 3.12+ | 12, 13 | x86_64, aarch64 |
+| Target | Ubuntu | Python wheel tag | CUDA wheel tag | Architecture |
+|--------|--------|------------------|----------------|--------------|
+| Desktop/server | 22.04 | `cp310` (Python 3.10) | `cu12`, `cu13` | x86_64 |
+| Desktop/server | 24.04 | `cp312-abi3` (Python 3.12+) | `cu12`, `cu13` | x86_64 |
+| Jetson Orin | 22.04 (JetPack 6.x) | `cp310` (Python 3.10) | `cu12` | aarch64 |
+| Jetson Thor | 24.04 (JetPack 7.x) | `cp312-abi3` (Python 3.12+) | `cu13` | aarch64 |
 
-**Prerequisite**: [CUDA Toolkit 12 or 13](https://developer.nvidia.com/cuda/toolkit) must be installed separately (not included in the wheels).
+Only the combinations listed above are provided as pre-built wheels. The `cp312-abi3` wheels use Python's stable ABI
+and are compatible with Python 3.12 and later. Other Python, CUDA, or Jetson combinations require an
+[installation from source](#install-from-source).
+
+**Prerequisite**: [CUDA Toolkit 12 or 13](https://developer.nvidia.com/cuda/toolkit) must be installed separately
+(not included in the wheels). Its major version must match the wheel's `cu12` or `cu13` tag.
 
 Official wheels include cuNLS support for `Multisensor` mode; no separate cuNLS installation is required.
 
 To install (virtual environment is recommended):
 
-1. Go to the [releases page](https://github.com/nvidia-isaac/cuVSLAM/releases).
-2. Download the wheel matching your CUDA version (`cu12` or `cu13`), Python version, and platform (`x86_64` or `aarch64`).
+1. Go to the [latest release](https://github.com/nvidia-isaac/cuVSLAM/releases/latest).
+2. Download the wheel matching the table above. On Jetson, also match the device family: Orin uses `cu12`/`cp310`;
+   Thor uses `cu13`/`cp312-abi3`.
 3. Install with pip:
 
 ```bash
@@ -144,8 +155,18 @@ CUVSLAM_BUILD_DIR=<path-to-cuvslam-build> pip install python/
 
 ## Pre-built Libraries
 
-Pre-built C++ libraries are available on the [releases page](https://github.com/nvidia-isaac/cuVSLAM/releases)
-for Ubuntu 22.04/24.04 on x86_64 and Jetson(aarch64) with CUDA 12 and CUDA 13.
+Pre-built C++ SDK archives are available on the
+[latest release](https://github.com/nvidia-isaac/cuVSLAM/releases/latest):
+
+| Target | Ubuntu | CUDA | Archive slug |
+|--------|--------|------|--------------|
+| Desktop/server | 22.04 or 24.04 | 12.6.3 or 13.2.0 | `x86_64-cuda<version>-ubuntu<version>` |
+| Jetson Orin | 22.04 (JetPack 6.x) | 12.6.3 | `orin-cuda12.6.3-ubuntu22.04` |
+| Jetson Thor | 24.04 (JetPack 7.x) | 13.0.1 | `thor-cuda13.0.1-ubuntu24.04` |
+
+The desktop/server row represents four archives covering both Ubuntu versions with both listed CUDA versions. Select
+the archive matching your target, Ubuntu version, and CUDA version. Each archive contains `bin/libcuvslam.so`,
+`bin/cuvslam_api_launcher`, and the public headers under `include/cuvslam/`.
 
 For Python usage, [pre-built wheels](#install-from-wheels) are the recommended approach.
 
@@ -266,8 +287,9 @@ RERUN=1 ctest --output-on-failure
 
 **Q**: What Python versions are supported by PyCuVSLAM?
 
-**A**: Pre-built wheels are available for Python 3.10 (Ubuntu 22.04) and Python 3.12 or later (Ubuntu 24.04+).
-When built from source, PyCuVSLAM supports Python 3.9 and later.
+**A**: Pre-built wheels use `cp310` for Python 3.10 on Ubuntu 22.04 and `cp312-abi3` for Python 3.12 or later on
+Ubuntu 24.04. Jetson wheels are limited to Orin with `cu12`/`cp310` and Thor with `cu13`/`cp312-abi3`; see the
+[wheel table](#install-from-wheels). When built from source, PyCuVSLAM supports Python 3.9 and later.
 
 
 # Troubleshooting

TROUBLESHOOTING.md

@@ -3,7 +3,8 @@
 ## Overview
 
 This document describes how to troubleshoot cuVSLAM when the system is installed and runs successfully but the computed
-pose is not sufficiently accurate. For installation or build issues, see the relevant sections of the documentation.
+pose is not sufficiently accurate. For installation or build issues, see
+[Install PyCuVSLAM](README.md#install-pycuvslam) and [Build cuVSLAM](README.md#build-cuvslam).
 
 ![Troubleshooting](doc/images/troubleshooting.png)
 
@@ -88,7 +89,7 @@ cuvslam::Odometry::Config::debug_dump_directory
 **Python API**
 
 ```python
-Odometry.Config.debug_dump_directory
+cuvslam.core.Odometry.Config.debug_dump_directory
 ```
 
 See [Python API Reference](https://nvidia-isaac.github.io/cuVSLAM/python/api.html#cuvslam.core.Odometry.Config.debug_dump_directory).
@@ -360,7 +361,7 @@ cuvslam::Odometry::Config::rectified_stereo_camera
 **Python API**
 
 ```python
-cuvslam.Odometry.Config.rectified_stereo_camera
+cuvslam.core.Odometry.Config.rectified_stereo_camera
 ```
 
 See [Python API Reference](https://nvidia-isaac.github.io/cuVSLAM/python/api.html#cuvslam.core.Odometry.Config.rectified_stereo_camera).
@@ -431,7 +432,7 @@ cuvslam::Odometry::Config::use_denoising
 **Python API**
 
 ```python
-Odometry.Config.use_denoising
+cuvslam.core.Odometry.Config.use_denoising
 ```
 
 See [Python API Reference](https://nvidia-isaac.github.io/cuVSLAM/python/api.html#cuvslam.core.Odometry.Config.use_denoising).
@@ -452,12 +453,12 @@ Mono → RGBD → Stereo Inertial → Stereo → Multicamera; Multisensor depend
 
 Multisensor (see [examples/multisensor/](examples/multisensor/README.md)) does not slot at a fixed
 position — its accuracy scales with the sensor set it is given. It requires at least one RGB-D
-camera or one overlapping camera pair and currently supports pinhole cameras only. A single
-RGB-D + IMU rig is roughly RGBD-class. A multi-stereo + RGB-D + IMU rig may approach or exceed
-Multicamera under favorable conditions, but this is an empirical expectation rather than a
-guarantee; benchmark the actual rig and environment. Use Multisensor when you have a
-mixed-camera-type rig or want IMU fusion on a non-stereo configuration; otherwise prefer the mode
-that exactly matches your rig.
+camera or one overlapping camera pair, a cuNLS-enabled build, and currently supports pinhole cameras only. Official
+release wheels include cuNLS. Multisensor is experimental and may be inaccurate or fail for some sensor configurations
+and scenes. A single RGB-D + IMU rig is roughly RGBD-class. A multi-stereo + RGB-D + IMU rig may approach or exceed
+Multicamera under favorable conditions, but this is an empirical expectation rather than a guarantee; benchmark the
+actual rig and environment. Use Multisensor when you have a mixed-camera-type rig or want IMU fusion on a non-stereo
+configuration; otherwise prefer the mode that exactly matches your rig.
 
 ### Adjust motion prediction
 
@@ -476,7 +477,7 @@ cuvslam::Odometry::Config::use_motion_model
 **Python API**
 
 ```python
-Odometry.Config.use_motion_model
+cuvslam.core.Odometry.Config.use_motion_model
 ```
 
 See [Python API Reference](https://nvidia-isaac.github.io/cuVSLAM/python/api.html#cuvslam.core.Odometry.Config.use_motion_model).

cuvslam-skills/cuvslam-onboard/SKILL.md

@@ -48,12 +48,17 @@ Once the user provides a path, use it consistently throughout all subsequent com
 
 ## 2. Install PyCuVSLAM (Quickest Path)
 
-Pre-built wheels from https://github.com/nvidia-isaac/cuVSLAM/releases:
+Pre-built wheels from https://github.com/nvidia-isaac/cuVSLAM/releases/latest:
 
-| Ubuntu | Python | CUDA | Arch |
-|--------|--------|------|------|
-| 22.04 | 3.10 | 12, 13 | x86_64, aarch64 |
-| 24.04+ | 3.12+ | 12, 13 | x86_64, aarch64 |
+| Target | Ubuntu | Python wheel tag | CUDA wheel tag | Arch |
+|--------|--------|------------------|----------------|------|
+| Desktop/server | 22.04 | `cp310` (Python 3.10) | `cu12`, `cu13` | x86_64 |
+| Desktop/server | 24.04 | `cp312-abi3` (Python 3.12+) | `cu12`, `cu13` | x86_64 |
+| Jetson Orin | 22.04 (JetPack 6.x) | `cp310` (Python 3.10) | `cu12` | aarch64 |
+| Jetson Thor | 24.04 (JetPack 7.x) | `cp312-abi3` (Python 3.12+) | `cu13` | aarch64 |
+
+Only these combinations are provided. The installed CUDA major must match the wheel's `cu12` or `cu13` tag; use a
+source build for other combinations.
 
 ```bash
 python3 -m venv .venv && source .venv/bin/activate

cuvslam-skills/cuvslam-troubleshoot/SKILL.md

@@ -40,7 +40,11 @@ cmake -S . -B build && cmake --build build --parallel $(nproc)
 ```
 
 ### PyCuVSLAM install
-Pre-built wheels: https://github.com/nvidia-isaac/cuVSLAM/releases
+Pre-built wheels: https://github.com/nvidia-isaac/cuVSLAM/releases/latest
+
+- x86_64: Ubuntu 22.04 / Python 3.10 has `cu12` and `cu13`; Ubuntu 24.04 / Python 3.12+ has `cu12` and `cu13`.
+- Jetson Orin: Ubuntu 22.04 / Python 3.10 / `cu12` only.
+- Jetson Thor: Ubuntu 24.04 / Python 3.12+ / `cu13` only.
 
 From source (after building C++ lib):
 ```bash
@@ -51,7 +55,7 @@ CUVSLAM_BUILD_DIR=<path-to-build> pip install python/
 - **Missing CUDA**: Set `CUDAToolkit_ROOT=/usr/local/cuda` or install CUDA Toolkit
 - **git-lfs not installed**: `apt install git-lfs && git lfs pull` (binary test data)
 - **CMake too old**: Need 3.19+
-- **Wheel ABI mismatch**: Match Python version (3.10 for Ubuntu 22.04, 3.12+ for 24.04)
+- **Wheel ABI mismatch**: Match the Python tag, CUDA major, architecture, and Jetson family using the matrix above.
 
 ## Tracking Issues
 

examples/multisensor/README.md

@@ -10,7 +10,7 @@ RGB-D cameras (`lcam_front`, `lcam_back`) plus a synthetic IMU from the
 
 ## Requirements
 
-- Use an official wheel or build with `USE_CUNLS=ON`.
+- Use an official release wheel, which includes cuNLS, or build from source with `USE_CUNLS=ON`.
 - Configure at least one RGB-D camera in `depth_camera_ids`, or provide at least one camera pair with overlapping
   frustums. A single RGB-D camera is valid, with or without an IMU.
 - Use pinhole cameras. Other camera models are not supported by the current solver.

examples/realsense/README.md

@@ -121,5 +121,6 @@ For a stereo + IMU multisensor smoke test using the same IR streams as the stere
 python3 run_vio.py
 ```
 
-> **Note:** Multisensor mode requires a cuNLS-enabled PyCuVSLAM build. The default source build enables cuNLS; if
-> cuVSLAM was configured with `-DUSE_CUNLS=OFF`, these multisensor examples are unavailable.
+> **Note:** Multisensor mode requires a cuNLS-enabled PyCuVSLAM build. Official release wheels include cuNLS, and the
+> default source build enables it. If cuVSLAM was configured with `-DUSE_CUNLS=OFF`, these multisensor examples are
+> unavailable.

python/docs/api.rst

@@ -65,7 +65,7 @@ Tracker class
 .. autoclass:: Tracker
    :members:
    :undoc-members:
-   :exclude-members: save_map, localize_in_map, OdometryMode, MulticameraMode
+   :exclude-members: OdometryMode, MulticameraMode
 
 Functions
 ---------

python/docs/index.rst

@@ -1,7 +1,7 @@
 Welcome to PyCuVSLAM API documentation!
 =======================================
 
-PyCuVSLAM is a Python bindings for the cuVSLAM (CUDA-accelerated Visual SLAM) library.
+PyCuVSLAM provides Python bindings for the cuVSLAM (CUDA-accelerated Visual SLAM) library.
 
 .. toctree::
    :maxdepth: 2