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Fuzsy

Member Since 07 Sep 2012
Offline Last Active Oct 16 2012 08:47 AM

Topics I've Started

Advanced pathfinding with robot in 3D

07 September 2012 - 10:37 AM

Hello,

My project:
I have a 2000 pounds real life robot with two arms. The arms are controlled by 15 motors and gets position feedback from 15 potentiometers. The robot is placed in a room with stationary objects which positions are known. The motors are only able to move with full speed.

Task:
Get the two arms of the robot from their current point to a selected point.

My current solution:
Currently the robot is moving by a big handmade table, but the problem is that if an object is moved the robot is going to collide. And it is almost impossible to imagine all possible situations.

Environment:
I have created a 3D simulation for the robot which I am planning to use when training the robot. The 3D simulation can detect collision with objects and between the two arms.

My question:
First I looked at some path finding algorithms like A* but with 15 motor in a 3D environment it is not very useful. Then I begin to look at neural network and Q-learning but I am not sure it is the right way to go. I think I need some kind of reinforcement learning.

My input and output could be something like:
Input:
15 x Current motor pos
15 x Goto pos
Obejects in room pos or the 3D simulation

Output:
15 x (maybe 5 states) sub positions for the motors

I am currently trying to figure out which network and learning method to use if I go with neural network and reinforcement learning.
Is it doable?

I hope someone can help me and maybe also point to an example.

Thank you in advance.

With best regards,
Peter

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