In this Godot Wild Jam #80 we had a team of 6 people. Two of which have never used the godot engine before, so it was a learning jam for them. This was a 9 day jam.
In this Weekend long game jam “PULS GAME JAM 2025“, we (a team of 3), have created a game in Unity. An engine that I have not used in a while and was kind of rusty. Nonetheless we have created a small cozy fishing game in which you are on a frozen lake that breaks over time.
Also we had time problems and two people could not participate in development for a day each.
While creating the concept of a new University module that has the students do a project with the Turtlebot3 robots and RL, a few ideas emerged. While evaluating different robot simulation tools for Reinforcement Learning, one in particular caught my eye: the Godot plugin “godot_rl_agents” by edbeeching. This was the result of a paper creating a bridge from Godot to RL libraries like StableBaselines3.
After trying the plugin it was clear that good result can be achieved quickly, there emerged the idea that students might be more encouraged learning the whole software stack when it involves a popular game engine instead of a “random” simulator with its own proprietary structure and configuration. So now it had to be proven that Sim2Real works with this Situation.
A friend modelled a “digital twin” of a turtlebot3, as the existing open source models usually used were very unoptimized and would hinder performance of actual training. It was purposefully minimal, but with accents to make it recognizable.
At first there was an example with just driving to a target point based on the map. No sensors needed. Simulation:
This was the first result:
The robot visible moves pretty badly in this clip. The reason which was later found: When the sent velocity commands would result in a jerky movement, the controller kind of rejects it and sometimes only does a part of the movement. Or sometimes no movement at all. To counteract this, the input has to be smoothed out beforehand to resist rejection from the controller.
Here is the next experiment with the lerp in mind:
This was the result:
The video shows that the robots performance can definitely be improved regarding stability and sensor calculations. Another big problem is also very visible here in that the small metal caster on the back of the turtlebot is very incompatible with the labs’ carpet flooring. This will be mitigated in the future with wooden plates that will make up the box’s floor.
In this 9 day long game jam, the team of three of us aimed to swap the main roles in the team. So the programmers were to create art, and the artist was supposed to code the game. We did not pull this through completely and had more of a mix towards the end. But we stepped out of our usual roles more than usual. We chose the “Godot Wild Jam #74” for this.
We did not explicitly use any of the possible “wild cards”.
This game is kind of a walking sim/narrative type.
In this 9 day long game jam, we wanted to created a more polished entry with our usual team of 4. We chose the “Godot Wild Jam #71” mainly because of it’s length, and with the potential of the wild cards giving us more ideas for a game.
This game is actually 4 games at once, and it plays with the idea of you being the “bad apple” that wants to punish the snake for eating all of the other apples.
In our second gamjam with godot, we formed a team of 4. The jam was “Mini Jame Gam #30“, and for it we created a tower defence game.
The gimmick is, that you can’t go too far away of the towers or they’re losing signal and stop firing. There are relay towers available to increase that range locally, but they’re expensive.
For this jam, we – a team of 4 – wanted to try the first jam with Godot instead of Unity. This was on the aftermath of the Unity pricing changes, so we wanted to finally give Godot a try.
In Life Support, you have to survive in your fragile submarine until you manage to surface. During your ascent your submarine is getting attacked by something, which you can temporarily scare off with the underwater siren.
For the “GMTK Game Jam 2023“, as a team of 4, we created a game that “plays itself”. We came up with the idea that you’d build a jump king like level, which an ai will try to play. The AI is presented as a rage game streamer.
In my university module “Higher Mathematics” we learned about projective space and the different representation with the hemisphere. (Or as we lovingly called it: “salad bowl”) This was part of the basics to understand Elliptic-curve cryptography.
Since I had a hard time wrapping my head around the secondary representation of projective space, I decided to create a visualizer in the game engine I was familiar with at the time: Unity3d. I built a very crude module that can creates a 2D plane with a translucent mesh which can morph between the two representations. And I also added the intersecting lines together with the points to visualize where the points are at all times. This helped me understand the topic more deeply and didn’t take too much time to make.
