nirvaannn

What did I do just now?

• Learned about floodfill through UCLA IEEE document
• Made a presentation to learn about it
• Wrote the base algorithm in pseudocode, next i have to do wall checking!

I got the MPU to work and added it to the turning
Now it uses encoder-based turning with MPU for checking/compensation

What did I do today?

• Used an I2C scan to make sure my MPU shows up
• Tested the MPU with help from Claude
• integrated this into my main code
• got it to log through the Serial
• tried to use it for turning but don’t know where to put it (interrupt, loop(), core 2 etc.)

i tried to add the LEDs’ 5v pins, but need to learn how to make the wires thicker using netclasses

I added a GitHub action to compile it into a pyinstaller binary (with help from Gemini)

I tried to add the MPU 6050 gyroscope in, but it just hangs & doesn’t give any readings so i don’t know why!

I experimented with the Kakao KANANA and LG EXAONE LLMs, as they’ve worked well in the past.

They are VERY fast even at high quantizations, but lose some world knowledge compared to Gemma3n or Phi4-mini.

What have i done since then?

• Updated the KittenTTS to use the new version of the model
• Tried the Phi-4 LLM which is quite good for world knowledge!

I added SK6812 LEDs to my PCB and routed their ground and data pins

Next will be to route the 5v IN pins for them!

What did I do today?

• Tried to use the Alpha Vantage API only to find out it was very rate limited
• Got AI to help me parse the other API data
• Test it and it works!

I tried to add text to show the name of the stocks and the percentage, but something is wrong! The stocks which are down are showing as 6% up.

I’m working with AI on how to parse the CSV better to avoid this.

What did I do today:

I added an HTML version so it doesn’t need Python Turtle anymore! This means I can deploy it to the web, and also view it on systems without Python.

My next step (using HTML) would be to show the name/details of the stocks when clicked on

What did I do:

• Started by parsing the stocks from yfinance
• Calculated up/down versus opening price
• Added Python turtle to visualize
• Changed the API to avoid rate limiting
• Add it to GitHub and write a README
• Try and package it using PyInstaller

A quick session where I:

• Hardcoded the maze to see how well it drives without PID
• Added a config menu so I don’t need to keep recompiling to change mode!

I worked for 1 hour to:

• get wall following to work
• rewrite the stateful wall following function
• calibrate different turning compensation and Kp/Kd values

and now it works (kind of…)

I added Bluetooth-based configuration to my robot - no more recompiling just to change Kp or Kd values!

Experimented with different models in llama.cpp and found Gemma 3n e2B to be the best balance of performance to world knowledge