Progress for week 6 (2020)
From Robin
(Difference between revisions)
(Ny side: == Nikolai == === This week's news === * Har fått hjelp av Ulysse og kan nå hente ut EMG data i Unity.) |
(→Wonho) |
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=== This week's news === | === This week's news === | ||
* Har fått hjelp av Ulysse og kan nå hente ut EMG data i Unity. | * Har fått hjelp av Ulysse og kan nå hente ut EMG data i Unity. | ||
+ | |||
+ | == Wonho == | ||
+ | === Accounting === | ||
+ | * new behaviour descriptor implemented - last position | ||
+ | ** the results are more promissing - 4 evolution processes generated same walking gait, low crawling ( this needs modification on fitness function ) | ||
+ | ** Needs longer evaluation for each genome to be effective | ||
+ | * Vanila NEAT - generates very uncoordinated and unstable gaits | ||
+ | * Tested some closed loop control scheme - setting its foot pattern or current joint angle as input to the network ( Risi uses current joint angle of upper joints ) | ||
+ | ** The results are mostly devastating - systems converging to stable state ( not moving at all ) after few iterations. | ||
+ | ** This used to work okay with MultiNEAT's CTRNN - perhaps there are some difference in implementation in neat-python | ||
+ | * Implementing MOEA | ||
+ | ** Tested Pareto front selection scheme on novelty archive ( currently limiting number of individuals since computation time increases exponentially ) | ||
+ | ** The results doesn't seem very different from before | ||
+ | ** Will implement this for NEAT reproduction process | ||
+ | * All experiments are recording git sha in the logger so that it can be regenerated later on | ||
+ | |||
+ | === Budget === | ||
+ | * Finish implementing MOEA in population reproduction process | ||
+ | * Create some graphs from recent experiments | ||
+ | |||
+ | == Tony == | ||
+ | === Budget === | ||
+ | Prøve på mobile robot med 2 ledd. (ikke 4 DOF) | ||
+ | |||
+ | === Accounting === | ||
+ | Hvordan kan dette på best muligvis overføres til vinkel/vinkelhastighet? | ||
+ | theta = w*f(x) + w*g(x) + ... hvor da f(x) og g(x) er motion-features kurver pluss mange i tillegg | ||
+ | |||
+ | [[Fil:Motion_features.png]] |
Current revision as of 09:36, 6 February 2020
Contents |
Nikolai
This week's news
- Har fått hjelp av Ulysse og kan nå hente ut EMG data i Unity.
Wonho
Accounting
- new behaviour descriptor implemented - last position
- the results are more promissing - 4 evolution processes generated same walking gait, low crawling ( this needs modification on fitness function )
- Needs longer evaluation for each genome to be effective
- Vanila NEAT - generates very uncoordinated and unstable gaits
- Tested some closed loop control scheme - setting its foot pattern or current joint angle as input to the network ( Risi uses current joint angle of upper joints )
- The results are mostly devastating - systems converging to stable state ( not moving at all ) after few iterations.
- This used to work okay with MultiNEAT's CTRNN - perhaps there are some difference in implementation in neat-python
- Implementing MOEA
- Tested Pareto front selection scheme on novelty archive ( currently limiting number of individuals since computation time increases exponentially )
- The results doesn't seem very different from before
- Will implement this for NEAT reproduction process
- All experiments are recording git sha in the logger so that it can be regenerated later on
Budget
- Finish implementing MOEA in population reproduction process
- Create some graphs from recent experiments
Tony
Budget
Prøve på mobile robot med 2 ledd. (ikke 4 DOF)
Accounting
Hvordan kan dette på best muligvis overføres til vinkel/vinkelhastighet? theta = w*f(x) + w*g(x) + ... hvor da f(x) og g(x) er motion-features kurver pluss mange i tillegg