Probabilistic Robotics

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staycoolish
Posts: 1
Joined: 01 Nov 2018, 19:58

Probabilistic Robotics

Post by staycoolish »

Hello,

I’ve learned about v-rep very recently. I need to find a simulation software that is capable of those:

1. Adding noise to sensor models, preferably a laser distance sensor.

2. Adding noise to motion model (kinematic) of a unicycle/dfferential drive, as we will use a simple unicycle model.

3. Commanding linear & angular velocities of the unicycle.

Now, I’ve seen that there are lots of different robots in v-rep, and I’ve seen Pioneer robot as differential drive. Most probably I will not be able to develop my unicycle model, since there is no enough time, but as far as you know are there any other differential drive models that we can download? Since I need a kinematic model, if Pioneer takes dynamics into account, I either need to access the equations of motion of it or download a kinematic model. Something tells me it’s very easy to access its equations of motions though.

My other question is, how can I add noise to motion and sensor models? I believe it must be very easy to do it for sensor, but for motion model, should I connect v-rep to matlab?

Finally, differential drive is controlled through its 2 wheels, but in our study we are required to command its linear & angular velocities. I know it’s not that hard, but again can I just use Matlab for achieving this? If there is a tutorial that you recommend to access the motion model of the robot, it would help a lot!

All of my questions are related to modifying EOM of the robot & adding sensor noise. However, I’ve written an essay accidentally.

Thanks in advance!

coppelia
Site Admin
Posts: 10336
Joined: 14 Dec 2012, 00:25

Re: Probabilistic Robotics

Post by coppelia »

Hello,

try to handle one task after the other. At the very first, make sure to follow a few tutorials. Also have a look how the various example models and scene are made/programmed. Then try to create a simple inverse pendulum as a beginning. Then move ahead step-by-step.

Cheers

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