User:Wonhol

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Goals

We are taking the start point from the paper from Risi,

Risi - Evolving flexible controller for locomotion

where locomotive controller for variable length legges were evolved with HyperNEAT approach.

The goal is to implement it on DyRet platform - where it has two actuator for each legges. Also other thing to consider will be taking account of Tegotae - where touch input is used as some kind of feedback to CPG. Risi had touch sensor as input to his substrate in the simulation.

Other aspect of it is to see if HyperNEAT approach is something plausible considering its complexity - some skeptical veiw on HyperNEAT. ie) simple CTRNN network with length of leg as one of the input.

Some of the tasks that could be done over the summer are

  * Read through DyRet doucumentation from robin wiki & github and set up a
    simulator enviorment
  * Theoretical understanding of Tegotae - is it plausible to embed it with
    CTRNN-substrate?
  * Experimenting with HyperNEAT libraries - Kyrre`s recommendation is
    "C++/Python MultiNEAT C++ with Python binding", otherwise Risi seems to

work with C# implementation -> perhaps it is a good idea to have a look.

OpenAI Gym Env for DyRET

https://github.uio.no/jorgehn/gym-dyret

HyperNEAT libraries

TODO

Plan for Fall semester

                                    2019
      September         October           November          December          
  Su  1  8 15 22 29        6 13 20 27        3 10 17 24     1  8 15 22 29   
  Mo  2  9 16 23 30        7 14 21 28        4 11 18 25     2  9 16 23 30   
  Tu  3 10 17 24        1  8 15 22 29        5 12 19 26     3 10 17 24 31   
  We  4 11 18 25        2  9 16 23 30        6 13 20 27     4 11 18 25      
  Th  5 12 19 26        3 10 17 24 31        7 14 21 28     5 12 19 26      
  Fr  6 13 20 27        4 11 18 25        1  8 15 22 29     6 13 20 27      
  Sa  7 14 21 28        5 12 19 26        2  9 16 23 30     7 14 21 28      
     35 36 37 38 39    39 40 41 42 43    43 44 45 46 47    48 49 50 51 52   

Remarks

Delivery in May 2020 Mid-term presentation in week 49


Week 35

OpenAI gym setup for DyRET

Get used to DyRET Env

  • input param for step : 12 np vector for joints, 8 for extension

HyperNEAT libraries

Lists of some promising ones

  • https://github.com/peter-ch/MultiNEAT
    • MultiNEAT, implemented in C++ with python bindings
    • good review from Stanley's website
    • https://gist.github.com/stefanopalmieri This guy has some nice examples binding multineat and gym env
    • installation
      • install boost
      • su as root
      • # export MN_BUILD=boost
      • # python3 setup.py build_ext
      • # python3 setup.py install **This casts broken library link error for boost**
      • Try with newer boost version since lboost_python36 is not included current version 1.61
  The Boost C++ Libraries were successfully built!
  The following directory should be added to compiler include paths:
   /home/ubuntu/boost/boost_1_71_0
  The following directory should be added to linker library paths:
   /home/ubuntu/boost/boost_1_71_0/stage/lib


Week 36

OpenAI gym setup HyperNEAT library test

by this point, familir with hyperNEAT packages and chosen one for the project OpenAI gym env setup for various experiments

Week 37

Experiment setup Implementing Risi's HyperNEAT on Dyret

Week 38

Experiment setup Implementing Risi's HyperNEAT on Dyret

Week 39

Experiment setup Implementing Risi's HyperNEAT on Dyret

Week 40

Experiment setup Implementing CPG style locomotive controller on Dyret

Week 41

Experiment setup Implementing CPG style locomotive controller on Dyret

Week 42

Experiment setup Implementing CPG style locomotive controller on Dyret

Week 43

Experiment run

Week 44

Experiment run

Week 45

Experiment run

Week 46

Experiment analysis

Week 47

Experiment analysis

Week 48

Experiment analysis

Week 49

Presenting first results

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