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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A new voxel layer leveraging modern 3D graphics tools to modernize navigation environmental representations
| Date | Stars |
|---|---|
| 2026-07-24 | 848 |
| 2026-07-25 | 848 |
| 2026-07-28 | 848 |
| 2026-07-30 | 848 |
| 2026-08-06 | 848 |
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# Spatio-Temporal Voxel Layer
This is a drop in replacement for the voxel_grid voxel representation of the environment. This package does a number of things to improve on the voxel grid package and extend the capabilities offered to the users, under a LGPL v2.1 license. Developed and maintained by [Steven Macenski](https://www.linkedin.com/in/steven-macenski-41a985101/) at [Simbe Robotics](http://www.simberobotics.com/).
This package sits on top of [OpenVDB](http://www.openvdb.org/), an open-source C++ library built by Dreamworks "comprising a novel hierarchical data structure and a suite of tools for the efficient storage and manipulation of sparse volumetric data discretized on three-dimensional grids. It is developed and maintained by DreamWorks Animation for use in volumetric applications typically encountered in feature film production."
Leveraging OpenVDB, we have the ability to efficiently maintain a 3 dimensional voxel-representative world space. We wrap this with ROS tools and interfaces to the [navigation stack](http://wiki.ros.org/navigation) to allow for use of this layer in standard ROS configurations. It is certainly possible to utilize this package without ROS/Navigation and I invite other competing methodologies to develop here and create interfaces.
Sample videos are shown below of a robot using **7 depth cameras** with less than 50% of a core, and another robot using a **VLP-16**.
7 Depth Cameras | VLP-16 LIDAR
:-------------------------:|:-------------------------:
 | 
We found in experimental trials with **6** 7hz dense stereo RGBD cameras we ran the major move_base process at **20-50%** nominal from **80-110%** on a 5th gen i7 CPU in the global costmap updating using the existing `voxel_layer`.
We've received feedback from users and have robots operating in the following environments with STVL:
- Retail
- Warehouses
- Factories
- Libraries
- Hospitals
- Hospitality
- RoboCup@Home
- Oil and Gas
Steve spoke at ROSCon 2018 about STVL and his presentation is [linked here](https://vimeo.com/292699571) (or click on image).
[](https://vimeo.com/292699571)
### Cite This Work
You can find this work [here](https://journals.sagepub.com/doi/10.1177/1729881420910530).
```
@article{doi:10.1177/1729881420910530,
author = {Steve Macenski and David Tsai and Max Feinberg},
title ={Spatio-temporal voxel layer: A view on robot perception for the dynamic world},
journal = {International Journal of Advanced Robotic Systems},
volume = {17},
number = {2},
year = {2020},
doi = {10.1177/1729881420910530},
URL = {https://doi.org/10.1177/1729881420910530}
}
```
## **Spatio**-
The Spatio in this package is the representation of the environment in a configurable `voxel_size` voxel grid stored and searched by OpenVDB.
In addition, buffered measurement readings have the option to run an approximate voxel grid filter, parameterizable at runtime in the configuration yamls. It is incredibly useful to reduce spikes in `move_base` cpu due to dense measurement readings when getting close to objects (i.e. more points), but does increase the overhead very slightly (1-2%) for nominal operations. It's a trade off but I recommend using it.
Below is an example a size of map that is **trivial** for the Spatio-Temportal Voxel Grid to maintain and render. This accounts for a 60,000 sq.ft. retail store with 710,765 voxels at a 0.05m resolution, with a size in memory of a mere 6.45MB.
## -**Temporal**
The Temporal in this package is the novel concept of `voxel_deExcerpt of 14,891 characters
Read on GitHub
Steve Macenski · @open-navigation · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:06e3678e19a2f590, topic:ros, readme:robotics, readme:manipulation