The main idea behind ROSplat is to make it easier to send and visualize Gaussians over the network, especially in robotics applications. For instance, imagine you're running a SLAM algorithm on a mobile robot and generating Gaussians as part of the mapping or localization process. With ROSplat, you can stream those Gaussians via ROS messages and visualize them live on another machine. It’s mostly a visualization tool that usess ROS for communication, making it accessible and convenient for robotics engineers and researchers already working within that ecosystem.

Just to clarify, ROSplat isn’t aiming to be faster than state-of-the-art rendering methods. The actual rendering is done with OpenGL, not ROS, so there’s no performance claim there. ROS is just used for the messaging, which does introduce a bit of overhead, but the benefit is in the ease of integration and live data sharing in robotics setups.

Also, I wrote a simple technical report explaining some things in more detail, you can find it in the repo!

Hope that clears things up a bit!

Just to clarify, ROSplat isn’t generating the Gaussians, it’s not a SLAM algorithm or a reconstruction tool. It’s purely a visualizer that uses ROS for message passing. The idea is that if you already have a system producing Gaussians (either live or precomputed), ROSplat lets you stream and view them in real time (as the ROS messages arrive).

So in your example, yes, you could upload a pre-baked GSplat, calibrate it to the robot’s frame, and use it for navigation or visualization. Or, if your ROS device is running something like SLAM, it can publish Gaussians as it goes. In both cases, ROSplat is just making them available for visualization, nothing more.

And I completely agree with you on your last comment. VR Gaussians are the way to go, I know that a company Varjo is currently working on them. Not sure if there's anything else that's available tho :/