---
title: General Robotics
created_date: 2024-10-24
updated_date: 2024-10-24
aliases:
tags:
---
# General Robotics

## Hardware

## Software

### AI and Machine Learning
#### World Model
https://www.1x.tech/discover/1x-world-model
https://worldmodels.github.io/
https://techterrain.substack.com/p/world-models-vs-kalman-filter?r=vudom&utm_campaign=post&utm_medium=web&triedRedirect=true

> [!Quote]- World Model Definition by Yann LeCunn
> Lots of confusion about what a world model is. Here is my definition:  
Given:  
> - an observation x(t)  
> - a previous estimate of the state of the world s(t)  
> - an action proposal a(t)  
> - a latent variable proposal z(t)  
>   
> A world model computes:  
> - representation: h(t) = Enc(x(t))  
> - prediction: s(t+1) = Pred( h(t), s(t), z(t), a(t) )  
> Where  
> - Enc() is an encoder (a trainable deterministic function, e.g. a neural net)  
> - Pred() is a hidden state predictor (also a trainable deterministic function).  
> - the latent variable z(t) represents the unknown information that would allow us to predict exactly what happens. It must be sampled from a distribution or or varied over a set. It parameterizes the set (or distribution) of plausible predictions.  
>   
> The trick is to train the entire thing from observation triplets (x(t),a(t),x(t+1)) while preventing the Encoder from collapsing to a trivial solution on which it ignores the input.  
>   
> Auto-regressive generative models (such as LLMs) are a simplified special case in which  
> 1. the Encoder is the identity function: h(t) = x(t),  
> 2. the state is a window of past inputs  
> 3. there is no action variable a(t)  
> 4. x(t) is discrete  
> 5. the Predictor computes a distribution over outcomes for x(t+1) and uses the latent z(t) to select one value from that distribution.  
> The equations reduce to:  
> s(t) = [x(t),x(t-1),...x(t-k)]  
> x(t+1) = Pred( s(t), z(t) )  
> There is no collapse issue in that case.

### Traditional Control
#### Model Predictive Control

### Perception
#### Kalman Filter

## Companies
- [Clearpath Robotics: Mobile Robots for Research & Development](https://clearpathrobotics.com/)