From f2ff10ae3af2df98c944e2837ccc2e3785174db0 Mon Sep 17 00:00:00 2001 From: scalinon <sylvain.calinon@idiap.ch> Date: Sat, 28 Dec 2019 09:42:49 +0100 Subject: [PATCH] Images updated --- README.md | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 77b4c69..a754527 100644 --- a/README.md +++ b/README.md @@ -246,9 +246,9 @@ All the examples are located in the main folder, and the functions are located i | [demo_TPproMP01.m](./demos/demo_TPproMP01.m) | [[1]](#ref-1) | Task-parameterized probabilistic movement primitives (TP-ProMP) | | [demo_TPtrajDistrib01.m](./demos/demo_TPtrajDistrib01.m) | [[1]](#ref-1) | Task-parameterized model with trajectory distribution and eigendecomposition | | [demo_TPtrajGMM01.m](./demos/demo_TPtrajGMM01.m) | [[1]](#ref-1) | Task-parameterized model with trajectory-GMM encoding | -| [demo_trajDistrib01.m](./demos/demo_trajDistrib01.m) | [[1]](#ref-1) | Stochastic sampling with Gaussian trajectory distribution | -| [demo_trajDistrib_differencingMatrix01.m](./demos/demo_trajDistrib_differencingMatrix01.m) | [[]]() | Conditioning on trajectory distribution constructed by differencing matrix, with via-point passing example | -| [demo_trajGMM01.m](./demos/demo_trajGMM01.m) | [[2]](#2) | Trajectory synthesis using a GMM with dynamic features (trajectory GMM) | +| [demo_trajDistrib01.m](./demos/demo_trajDistrib01.m) | [[2]](#ref-2) | Stochastic sampling with Gaussian trajectory distribution | +| [demo_trajDistrib_differencingMatrix01.m](./demos/demo_trajDistrib_differencingMatrix01.m) | [[2]](#ref-2) | Conditioning on trajectory distribution constructed by differencing matrix, with via-point passing example | +| [demo_trajGMM01.m](./demos/demo_trajGMM01.m) | [[2]](#ref-2) | Trajectory synthesis using a GMM with dynamic features (trajectory GMM) | | [demo_trajGMM02.m](./demos/demo_trajGMM02.m) | [[2]](#ref-2) | Trajectory synthesis with a GMM with dynamic features (trajectory GMM), where the GMM is learned from trajectory examples || | [demo_trajHSMM01.m](./demos/demo_trajHSMM01.m) | [[2]](#ref-2) | Trajectory synthesis with an HSMM with dynamic features (trajectory-HSMM) | | [demo_trajHSMM_adaptiveDuration01.m](./demos/demo_trajHSMM_adaptiveDuration01.m) | [[9]](#ref-9) | Hidden semi-Markov model with adaptive duration | @@ -266,12 +266,13 @@ Calinon, S. (2016). <strong>A Tutorial on Task-Parameterized Movement Learning a <br> (Ref. for GMM, TP-GMM, MFA, MPPCA, GPR, trajGMM) -#### [2] -Calinon, S. and Lee, D. (2019). <strong>Learning Control</strong>. Vadakkepat, P. and Goswami, A. (eds.). Humanoid Robotics: a Reference, pp. 1261-1312. Springer. +<div id="ref-2"> +<p>[2] Calinon, S. and Lee, D. (2019). <strong>Learning Control</strong>. Vadakkepat, P. and Goswami, A. (eds.). Humanoid Robotics: a Reference, pp. 1261-1312. Springer. [[pdf]](http://calinon.ch/papers/Calinon-Lee-learningControl.pdf) [[bib]](http://calinon.ch/papers/Calinon-Lee-learningControl.bib) -<br> -(Ref. for MPC, LQR, HMM, HSMM) +</p> +<strong>(Ref. for MPC, LQR, HMM, HSMM)</strong> +</div> #### [3] (Ref. for Riemannian manifolds) Calinon, S. and Jaquier, N. (2019). <strong>Gaussians on Riemannian Manifolds for Robot Learning and Adaptive Control</strong>. arXiv:1909.05946. -- GitLab