56 lines
2.1 KiB
Markdown
56 lines
2.1 KiB
Markdown
---
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title: General Robotics
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created_date: 2024-10-24
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updated_date: 2024-10-24
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aliases:
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tags:
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---
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# General Robotics
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## Hardware
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## Software
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### AI and Machine Learning
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#### World Model
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https://www.1x.tech/discover/1x-world-model
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https://worldmodels.github.io/
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https://techterrain.substack.com/p/world-models-vs-kalman-filter?r=vudom&utm_campaign=post&utm_medium=web&triedRedirect=true
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> [!Quote]- World Model Definition by Yann LeCunn
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> Lots of confusion about what a world model is. Here is my definition:
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Given:
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> - an observation x(t)
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> - a previous estimate of the state of the world s(t)
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> - an action proposal a(t)
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> - a latent variable proposal z(t)
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>
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> A world model computes:
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> - representation: h(t) = Enc(x(t))
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> - prediction: s(t+1) = Pred( h(t), s(t), z(t), a(t) )
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> Where
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> - Enc() is an encoder (a trainable deterministic function, e.g. a neural net)
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> - Pred() is a hidden state predictor (also a trainable deterministic function).
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> - 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.
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>
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> 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.
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>
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> Auto-regressive generative models (such as LLMs) are a simplified special case in which
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> 1. the Encoder is the identity function: h(t) = x(t),
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> 2. the state is a window of past inputs
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> 3. there is no action variable a(t)
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> 4. x(t) is discrete
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> 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.
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> The equations reduce to:
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> s(t) = [x(t),x(t-1),...x(t-k)]
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> x(t+1) = Pred( s(t), z(t) )
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> There is no collapse issue in that case.
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### Traditional Control
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#### Model Predictive Control
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### Perception
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#### Kalman Filter
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## Companies
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- [Clearpath Robotics: Mobile Robots for Research & Development](https://clearpathrobotics.com/) |