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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble gxf_isaac_occupancy_grid_projector isaac_ros_bi3d_freespace |
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Repository Summary
Description | NVIDIA-accelerated, deep-learned freespace segmentation |
Checkout URI | https://github.com/nvidia-isaac-ros/isaac_ros_freespace_segmentation.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-02-28 |
Dev Status | UNKNOWN |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | deep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Packages
Name | Version |
---|---|
gxf_isaac_occupancy_grid_projector | 3.2.5 |
isaac_ros_bi3d_freespace | 3.2.5 |
README
Isaac ROS Freespace Segmentation
NVIDIA-accelerated, deep-learned freespace segmentation
Overview
Isaac ROS Freespace Segmentation contains an ROS 2 package to produce occupancy grids for navigation. By processing a freespace segmentation mask with the pose of the robot relative to the ground, Bi3D Freespace produces an occupancy grid for Nav2, which is used to avoid obstacles during navigation. This package is GPU accelerated to provide real-time, low latency results in a robotics application. Bi3D Freespace provides an additional occupancy grid source for mobile robots (ground based).
isaac_ros_bi3d
is used in a graph of nodes to provide a freespace
segmentation mask as one output from a time-synchronized input left and
right stereo image pair. The freespace mask is used by
isaac_ros_bi3d_freespace
with TF pose of the camera relative to the
ground to compute planar freespace into an occupancy grid as input to
Nav2.
There are multiple methods to predict the occupancy grid as an input to navigation. None of these methods are perfect; each has limitations on the accuracy of its estimate from the sensor providing measured observations. Each sensor has a unique field of view, range to provide its measured view of the world, and corresponding areas it does not measure. Bi3D Freespace provides a diverse approach to identifying obstacles from freespace. Stereo camera input used for this function is diverse relative to lidar, and has a better vertical field of view than most lidar units, allowing for perception of low lying obstacles that lidar can miss. Bi3D Freespace provides a robust, vision-based complement to lidar occupancy scanning.
Isaac ROS NITROS Acceleration
This package is powered by NVIDIA Isaac Transport for ROS (NITROS), which leverages type adaptation and negotiation to optimize message formats and dramatically accelerate communication between participating nodes.
Performance
Sample Graph |
Input Size |
AGX Orin |
Orin NX |
Orin Nano Super 8GB |
x86_64 w/ RTX 4090 |
---|---|---|---|---|---|
Freespace Segmentation Node |
576p |
3340 fps 1.7 ms @ 30Hz |
2530 fps 1.5 ms @ 30Hz |
2140 fps 1.9 ms @ 30Hz |
3500 fps 0.44 ms @ 30Hz |
Freespace Segmentation Graph |
576p |
40.3 fps 79 ms @ 30Hz |
27.6 fps 98 ms @ 30Hz |
31.8 fps 55 ms @ 30Hz |
102 fps 30 ms @ 30Hz |
Documentation
Please visit the Isaac ROS Documentation to learn how to use this repository.
Packages
Latest
Update 2024-12-10: Update to be compatible with JetPack 6.1
CONTRIBUTING
Isaac ROS Contribution Rules
Any contribution that you make to this repository will be under the Apache 2 License, as dictated by that license:
5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.
Contributors must sign-off each commit by adding a Signed-off-by: ...
line to commit messages to certify that they have the right to submit
the code they are contributing to the project according to the
Developer Certificate of Origin (DCO).
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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isaac_ros_freespace_segmentation repositorydeep-neural-networks deep-learning gpu nvidia freespace jetson ros2 ros2-humble |
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