Adaptive Arena

In this demo, Eman walks through recent updates to his robotics project, focusing on improvements to the camera setup and the robot configuration within the Isaac Lab environment. These changes help create a more stable and accurate system for perception, simulation, and future autonomous development.

In this update Eman showcases a major update to his robotics project. The robot can now move autonomously toward rewards with high accuracy, making decisions based on its environment rather than following predefined paths.

Check out Muhammad Eman Aftab ’s work from our Budapest research lab. Eman is one of our AI researchers, working on inspiring research projects and, most importantly, building in public, with the good, the bad, and the ugly!

In this demo, Eman walks through two key steps in advancing his vision-based control system. First, he calibrates the camera, upgrading the model from a 2D guess-based approach to a proper 3D calibration setup for more accurate perception. He then sets up the Isaac environment, laying the groundwork for testing, simulation, and future autonomous behavior.

In this introductory video, Eman shares the vision behind his project at the Lightbloom AI Lab in Budapest: building a system that can transform simple hand-drawn sketches into fully playable board games.

This week in the Lightbloom Lab, Eman is showcasing a new vision-driven control system that lets a robot move entirely on its own by reading printed signs. By pointing a camera at simple symbols on paper, the system can interpret the command in real time and adjust its movement without any manual input.

Join us inside the Lightbloom AI Lab in Budapest as our researcher, Eman, demonstrates the latest updates to our Sketch-to-Game Generator.