title="A Tutorial on Task-Parameterized Movement Learning and Retrieval",
journal="Intelligent Service Robotics",
publisher="Springer Berlin Heidelberg",
issn="1861-2776",
doi="10.1007/s11370-015-0187-9",
year="2016",
volume="9",
number="1",
pages="1--29"
pages="1--29",
doi="10.1007/s11370-015-0187-9",
}
```
* HMM, HSMM:
```
@inproceedings{Calinon14ICRA,
author="Calinon, S. and Bruno, D. and Caldwell, D. G.",
title="A task-parameterized probabilistic model with minimal intervention control",
booktitle="Proc. {IEEE} Intl Conf. on Robotics and Automation ({ICRA})",
year="2014",
month="May-June",
address="Hong Kong, China",
pages="3339--3344"
@article{Rozo16Frontiers,
author="Rozo, L. and Silv\'erio, J. and Calinon, S. and Caldwell, D. G.",
title="Learning Controllers for Reactive and Proactive Behaviors in Human-Robot Collaboration",
journal="Frontiers in Robotics and {AI}",
year="2016",
month="June",
volume="3",
number="30",
pages="1--11",
doi="10.3389/frobt.2016.00030"
}
```
* Semi-tied covariances in mixture models:
@article{Tanwani16RAL,
author="Tanwani, A. K. and Calinon, S.",
title="Learning Robot Manipulation Tasks with Task-Parameterized Semi-Tied Hidden Semi-{M}arkov Model",
journal="{IEEE} Robotics and Automation Letters ({RA-L})",
year="2016",
month="January",
volume="1",
number="1",
pages="235--242",
doi="10.1109/LRA.2016.2517825"
}
* DP-means:
@article{Bruno16AURO,
author="Bruno, D. and Calinon, S. and Caldwell, D. G.",
title="Learning Autonomous Behaviours for the Body of a Flexible Surgical Robot",
journal="Autonomous Robots",
year="2016",
volume="",
number="",
pages="",
doi="10.1007/s10514-016-9544-6",
}
### Compatibility
The codes are compatible with both Matlab and GNU Octave.
...
...
@@ -77,13 +106,16 @@ All the examples are located in the main folder, and the functions are located i
| demo_affineTransform01 | Affine transformations of raw data as pre-processing step to train a task-parameterized model |
| demo_batchLQR01 | Controller retrieval through a batch solution of linear quadratic optimal control (unconstrained linear MPC), by relying on a Gaussian mixture model (GMM) encoding of position and velocity data (see also demo_iterativeLQR01) |
| demo_batchLQR02 | Same as demo_batchLQR01 but with only position data |
| demo_batchLQR_augmSigma01 | Batch LQR with augmented covariance to transform a tracking problem to a regulation problem |
| demo_DMP01 | Dynamic movement primitive (DMP) encoding with radial basis functions |
| demo_DMP02 | Generalization of dynamic movement primitive (DMP) with polynomial fitting using radial basis functions |
| demo_DMP_GMR01 | Emulation of a standard dynamic movement primitive (DMP) by using a GMM with diagonal covariance matrix, and retrieval computed through Gaussian mixture regression (GMR) |
| demo_DMP_GMR02 | Same as demo_DMP_GMR01 but with full covariance matrices coordinating the different variables |
| demo_DMP_GMR03 | Same as demo_DMP_GMR02 but with GMR used to regenerate the path of a spring-damper system instead of encoding the nonlinear forcing term |
| demo_DMP_GMR04 | Same as demo_DMP_GMR03 by using the task-parameterized model formalism |
| demo_DMP_GMR_LQR01 | Same as demo_DMP_GMR04 but with LQR used to refine the parameters of the spring-damper system |
| demo_DMP_GMR_LQR02 | Same as demo_DMP_GMR_LQR01 with perturbations added to show the benefit of full covariance to coordinate disturbance rejection |
| demo_DPMeans_Online01 | Online clustering with DP-Means algorithm |
| demo_DPMeans_Online01 | Online clustering with DP-means algorithm |
| demo_DSGMR01 | Gaussian mixture model (GMM), with Gaussian mixture regression(GMR) and dynamical systems used for reproduction, with decay variable used as input (as in DMP) |
| demo_DTW01 | Trajectory realignment through dynamic time warping (DTW) |
| demo_GMM01 | Gaussian mixture model (GMM) parameters estimation |
...
...
@@ -110,7 +142,7 @@ All the examples are located in the main folder, and the functions are located i
| demo_TPGP01 | Task-parameterized Gaussian process regression (TP-GPR) |
| demo_TPHDDC01 | Task-parameterized high dimensional data clustering (TP-HDDC) |
| demo_TPMFA01 | Task-parameterized mixture of factor analyzers (TP-MFA), without motion retrieval |
|demo_TPMPC01 | Task-parameterized model encoding position data, with MPC used to track the associated stepwise reference path |
|demo_TPMPC01 | Task-parameterized model encoding position data, with MPC used to track the associated stepwise reference path |
| demo_TPMPC02 | Same as demo_TPMPC01 with a generalized version of MPC used to track associated stepwise reference paths in multiple frames |
| demo_TPMPPCA01 | Task-parameterized mixture of probabilistic principal component analyzers (TP-MPPCA) |
| demo_TPtrajGMM01 | Task-parameterized model with trajectory-GMM encoding |
