Progress for week 39 (2019)
From Robin
Contents |
Wonho
Budget
- Find out how to customize CPPN in MultiNEAT - Risi has extra input parameter for leg length
- Document setting up dev. env process
- Look into Docker generation
- Try simple HyperNEAT on DyRET env. - doesn't have to take account on leg length
Accounting
- TODO
Tony
Budget
- Get into a robot simulation program either webots, v-rep and etc...
Accounting
- Have worked a lot on V-rep robot simulator. So far things have looked quite promising.
- Managed to establish connection between server and client, i.e. V-rep allows one to send and receive commands between console windows. This is supported in Python which means I can take the outputs from neural network onto the robot with relative ease.
- Have applied MDN-layer, a mixture density layer to the DNN to solve inverse kinematics which samples from probability distribution for example an x-input can have multiple values for y. Taking the average/mean will therefore be a problem, MDN solves this issue. Works perfectly fine in 2D, but with adding an extra dimension i.e. 'Z' and the neural model cannot estimate. Problem could be the loss function. Wll investigate this further next work.
Nikolai
Budget
- Teste ulike tracking metoder
- Lage et simpelt AR system
Accounting
- Har laget en image tracking AR app til android.
- Ikke klart å finne et robust tracking system som kan brukes i Unity.