VVV09 Kinematic, my friend
The aim subject is the learning of the forward kinematic model.
Why learn the model, we already have an analytic method ?
- A human like approach.
- To validate the feasibility of such kind of learning.
Why the forward model ?
- To keep all the information of the model (i.e infinity of pseudo-inverse of the Jacobian, null space computation).
Why the kinematic ?
- Because the geometric model is not easily invertible.
What kind of algorithm is using ?
- LWPR, (Locally Weighted Projection Regression) [Vijayakumar 2005]. A powerfull online learning algorithm based on multiple linear regression computation in the space the most adapted (PLS).
What are the results ?
- The model is learned and uses "successfully" on the robot.
What about the "keep all the information" ?
- With the learned model we are able to control two end-effectors with a priority on one of them.
So, what did you do here ?
- I tried to learn the model ... without the model but with the vision.
- I have learned the model by attended motor babbling (As we play with the "end effector" of a baby).
- I "wanted" to be able to track two objects (my end effector and another object ... But it is apparently not so easy :p) in order to complete the learning of the model still as if we were playing with a child.