[mlpack] Robotic Arm - GSoC Project Idea

[Vaibhav Jain]

Hey Marcus,
I think this would be a good approach to work on this project:
# First we need to find the required final coordinates of the object (in
the simulation we would already know that, but in the real world, we need
to use some 3D camera).
# Then we can find the optimal path using trajectory planning techniques
# After that we can find the joint angles using inverse kinematics
# Using these joint angles, we can train our model

For learning manipulator kinematics/dynamics, lectures by Prof. Oussama
Khatib at Stanford, are very good. The book "Introduction to Robotics:
Mechanics and Control" by J. Craig is also very good.
For simulation, the environments you suggested would be surely helpful.
Although, I need to work a little bit more to see the extent to which they
can be used.

I wanted to you ask how to train mlpack models on large datasets on cloud.
It would help me to create a detailed timeline for my proposal.
Please let me know what you think.

On Wed, Feb 28, 2018 at 6:22 PM, Marcus Edel <marcus.edel at fu-berlin.de>
wrote:

> Hello Vaibhav,
>
> OpenAI released a couple of robotics environments wich could be
> interesting:
> https://github.com/openai/gym/tree/master/gym/envs/robotics
>
> Best,
> Marcus
>
> On 27. Feb 2018, at 17:00, Vaibhav Jain <vabsweb at gmail.com> wrote:
>
> Hello Marcus,
> Thanks for this resource. I will sure check it out. In the meantime, I
> will also research some other previous similar projects.
>
>
> On Feb 27, 2018 03:36, "Marcus Edel" <marcus.edel at fu-berlin.de> wrote:
>
> Hello Vaibhav,
>
> thanks for the input, I agree ROS is definitely a good option to get
> started,
> the available resources is just one point. My initial idea was to
> integrate the
> simulator in the OpenAI Gym framework, mlpack already follows the gym
> interface
> so the interaction is already in place, but I think we could use the Gazebo
> extension for Gym to get it working. This looks promising
> (https://github.com/erlerobot/gym-gazebo). Not sure the install process is
> straightforward, in the best case we can install everything with a few
> clicks
> and most packages are available for a bunch of distributions.
>
> Thanks,
> Marcus
>
>
> __
> Vaibhav Jain
>
>
>

Regards,
-- 
- Vaibhav Jain
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://knife.lugatgt.org/pipermail/mlpack/attachments/20180312/b68c8952/attachment-0001.html>