Ragdoll physics without 3rd party libraries

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Discussion Overview

The discussion revolves around programming ragdoll physics without the use of third-party libraries, exploring algorithms and resources related to this topic. Participants also touch on related concepts such as genetic algorithms and neural networks in the context of simulating movement.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant inquires about resources for ragdoll physics programming without third-party libraries.
  • Several links to resources are provided, including academic papers and tutorials on related topics.
  • Another participant shares their project idea of simulating a robot learning to walk using genetic algorithms, expressing challenges with input and output definitions for neural networks.
  • Concerns are raised about the feasibility of building a body simulator from scratch, suggesting that using third-party libraries could save time and effort.
  • Discussion includes the idea that walking can be learned through logic and automatic processes, with references to using least squares regression for learning physics laws.
  • A participant mentions the use of mathematical tools to correlate inputs and outputs in learning physical laws, referencing specific algorithms and publications related to regression.
  • Questions arise about the motivations for avoiding third-party libraries, with one participant arguing for their utility in handling complex mathematical modeling.
  • There is a light-hearted exchange regarding the use of accented characters in writing, with a participant explaining their French background.

Areas of Agreement / Disagreement

Participants express differing views on the necessity and practicality of using third-party libraries for ragdoll physics programming. Some advocate for their use due to the complexity of the underlying math, while others argue for the benefits of building a custom solution.

Contextual Notes

The discussion includes various assumptions about the capabilities and limitations of different approaches to simulating physics, as well as the potential challenges in implementing algorithms without established libraries.

Superposed_Cat
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Hey all, are there any resources available online on rag doll physics programming without 3rd party libraries? the algorithms etc? Any help appreciated.
 
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Greg Bernhardt said:
What kind of project are you working on?
Make a simulated robot learn to walk with genetic algorithms. I wanted to do it with neural networks but couldn't figure out what to make the inputs and outputs
 
Ones you have a simulator, i personally think that it's not a good idea to not use a third party library. You will loose a lot of time to build another (and another) body simulator. I think that you need to concentrate on the interesting part. For the input and output it depend on the library, you can use joint angle and body position and the neural net will give in output the joint momentum, or the joint angle speed to control the caracter.

Previously i try genetic algorithm for this kind of task and it doesn't work well because learning is very long. Walk can be learned by logic, automatic. You can automaticaly learn physics law with généric model regression like least square regression and then use it to search how to move using a tree to explore the configuration space.
 
kroni said:
Previously i try genetic algorithm for this kind of task and it doesn't work well because learning is very long. Walk can be learned by logic, automatic. You can automaticaly learn physics law with généric model regression like least square regression and then use it to search how to move using a tree to explore the configuration space.

Could you elaborate on the least squares technique for learning physics please?
 
Genetic algorithm and neural network are généric function interpolator and regression. To learn physics you can use mathématical tools that fit the observation and make a correlation with the input. So for a value of the input you can get a value for the output, the objective is to learn physical law (what is the consequence of an action). In a second step you can use this model to act on the environement. I know a publication about LWPR, a generic high dimension regression algorithm, and a paper about physics model learning.

Link are :
http://wcms.inf.ed.ac.uk/ipab/slmc/research/lwpr/lwpr-tutorial
http://homepages.inf.ed.ac.uk/svijayak/publications/vijayakumar-ICML2000.pdf
 
thanks, out of interest why do you type your 'e's like this? not complaining they are whimsical :P

kroni said:
é
 
Superposed_Cat said:
Hey all, are there any resources available online on rag doll physics programming without 3rd party libraries?
Why do you want to avoid 3rd party libraries? You're using a compiler. Why aren't you using machine language? What's the difference between a 3rd party library and a compiler?

There's a lot to be said for those 3rd party libraries. The underlying math can be very tricky. Properly modeling multi-body physics is trickier yet. The odds you'll get it right are slim to none. There are very good 3rd party libraries that are free, get it right, and are fast.
 
  • #10
  • #11
I use "é" because i am french and we also use e , é , é , ê , a , à , ç. It seem funny but it's not, it's an boring language.
 
  • #12
lol
 

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