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Messages - santacide

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Newbie / Re: Hello, and opinions on robotics
« on: May 22, 2015, 04:57:54 PM »
You probably don't want just the amount of battery left to affect behavior or the correct solution is to just stay in the charger ("the only winning move is not to play...").  At the simplest you could also have it try to move towards sounds.  Balancing that "instinct" with the battery "instinct" should create interesting behavior.

That actually gives me a great idea... using battery voltage for reward, the neural network could experience "pain" if the voltage goes too low *or* too high, meaning remaining in the charger for too long will be painful (kind of like "overeating").

Right now I'm reading the neural networks and deep learning link you gave, it seems rather helpful though at this point I'm not sure a cpld/fpga would work, considering there's no way to change the weights in a neural network on one without reprogramming it, unless memory is also programmed into the fpga, meaning it must be that much more complex...

Anyway, most of what remains to be worked out is hardware, so I'll be heading out. If you guys care to see what the results are I'd be happy to show it here once it's done. Also, feel free to post more suggestions if you think of anything, I'll still check by from time to time. :)

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Newbie / Re: Hello, and opinions on robotics
« on: May 20, 2015, 08:02:56 PM »
Hey Numsgil,

Thanks for the suggestions, those are actually great ideas. I've done some more planning/research and made the design a bit more concrete...

1: Reward/Pain is a result of the amount of battery charge remaining.

2: Inputs are the battery meter, 2 light and 2 tactile sensors. The charging station will be located under a light source, such that if the battery meter shows a low charge the robot will be able to seek out the light source.

3: I'm planning on having the robot learn in the "real world", not in a simulation, though like you said that would certainly be faster.

4: I'm still not sure of implementation, though I'm leaning towards a neural network just for biomimicry. I'm thinking I'll simulate the network in vhdl on a small cpld/fpga, with the inputs and outputs being pre- and post- processed by a microcontroller.

Note that many things about this will be "intelligently designed", such as the body, with the only purpose of the neural network being for behaviour. Similar to darwinbots.

I've also done some research on the C. Elegans neural connectome and found two things relevant to this:

1: The C. Elegans neural network has a fixed number of neurons and a fixed number of connections. However, it can learn by strengthening/weakening the pre-existing synapses.

2: There is a ridiculous amount of recursion. Sensory neurons will effect both motor neurons and interneurons, which will effect each other, and in many cases send signals back to the sensory neurons. This is probably how the worm can learn using only a fixed amount of neurons and connections.

So, I'm thinking of hard-coding a neural network in an fpga/cpld and having the robot learn by changing the neuronal weights. At this point I am unsure of how to automate the weight-changing though.

I guess my main question at this point is, how would you go about this?

Thanks again for the help.

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Newbie / Hello, and opinions on robotics
« on: May 13, 2015, 03:47:46 AM »
Greetings!

Although this question is not strictly related to DB, I was hoping I could have your insight... I have been an enthusiast in BEAM robotics for a while (click here for details) but have started to shift away from analog circuits to microprocessor designs in order to simulate greater complexity. Although using a processor means I could just directly program in behavior, that somewhat defeats the purpose of making the robot biomorphic.

Basically the only requirements are that the design be biologically-inspired in some way and fits on an arduino-like microcontroller (atmel, picaxe, parallax propeller), though the ability to learn and give time-dependent output would be nice too. The sensors/inputs will not be very complex, being something along the lines of 2 microphones, 2 light sensors and 3 touch sensors, while the output would be movement direction, pan/tilt for the light/sound sensors, and a speaker. By time-dependent output I'm refering to the ability to give output that changes with time as well as sensor input, such as leg motor movement (where the leg must move up for say, half a second, move forward, move down, move back, and repeat).

I've been considering a lot of options, such as cellular automata, neural networks, genetic algorithms, etc... But I was hoping I could have your viewpoint as well. Thoughts?

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