# A deep learning project - the model fails to predict angles

Hello everyone
I have a project that deals with multi agent.
I will write briefly about the project and then indicate where I get stuck and what doesn’t work for me
I am currently running the algorithm on one robot
I have a simple robot consisting of a body (center of mass) and 2 legs and its goal is to reach a certain location while navigating a maze that is on a grid.
The catch here is that the legs can only step on the vertices of the grid.
So what have I done so far?!
I used the RRT algorithm and put a bunch of different (random) start and end locations into it
I converted the route obtained from the RRT to a discrete route (which will be the route of the center of mass)
Then I used all sorts of functions and chose for each time step the best point to place each leg on the grid
I created a csv file containing the following:

1. Angle from the center of mass to the target (which will actually be a kind of direction vector)
2. The angle of the legs (how the legs are positioned in relation to each other)
3. 25 binary values ​​that represent the local environment of the robot in the maze (indicate whether there is an obstacle or not)
4. The desired angle of the legs position (for the next step)
5. dx, dy of the center of mass (that is, how much it must advance in the X axis and Y axis in relation to its current position. It is important to note that this is a relative value and not an absolute position in space

1-3 indicate the input to the network
4-5 indicate the output of the network (the actions)

Because of the problem with using angles (as a result of their periodicity, 0=360 or the distance between angle 1 and angle 359 is not large), I decided to use sin, cos of the angle
That’s why my input is size 29
My output is size 4

It is very, very difficult for me to find a proper prediction of the angles. I get R^2=30% which is very low and does not indicate learning
-I performed normalization, deletion of abnormal values, etc.
(Since there are not many angles of the position of the legs, I tried to divide the problem into 2 - classification for the output of the angles and regression for the output of the positions, but still it does not work well)

Does anyone have an idea what I should do? How to treat data?
Which model to work with? Maybe add other inputs to the network?
How should I treat the angles? I’m sure that’s where the problem is
I get a very bad confusion matrix

Thank you very much everyone!!!