Updated installation instructions

README.md

-# Minimalist GUI for PbDlib
+# PbDlib-cpp
 
-This GUI is intended to be used with the pbdlib library available at
-https://gitlab.idiap.ch/rli/pbdlib
+PbDlib-cpp is a set of tools in C++ combining statistical learning, optimal control and differential geometry for programming-by-demonstration applications.
+Other versions of the library are available at http://www.idiap.ch/software/pbdlib/ (in Matlab, C++ and Python).
 
 ### Contributors
 
-Sylvain Calinon, Ioannis Havoutis, Ajay Tanwani, Emmanuel Pignat, Fabien Crepon,
-Daniel Berio, Philip Abbet
+Sylvain Calinon, Ioannis Havoutis, Ajay Tanwani, Emmanuel Pignat, Fabien Crepon, Daniel Berio, Philip Abbet
 
-### Prerequisite
+This work was in part supported by the DexROV project through the EC H2020 programme (Grant \#635491).
 
-The program requires glfw3 (modern lightweight and portable library for managing
-OpenGL contexts, windows and inputs, similar to glut but better!). 
+### Prerequisite
 
-It also requires epoxy (OpenGL function pointer management library) in some of the examples.
+The program requires glfw3 (lightweight and portable library for managing OpenGL contexts, windows and inputs). 
 
 ### Compilation
 
 ```
-cd pbdlib_gui
+cd pbdlib-cpp
 mkdir build
 cd build
 cmake ..
 make
 ```
 
-### epoxy package install
-
-```
-sudo apt-get install libepoxy-dev
-```
-
 ### glfw3 deb package install
 
 ```
@@ -195,9 +187,6 @@ This project will build a number of executables, as listed in the table below.
 
 | Filename | ref. | Description |
 |----------|------|-------------|
-| demo_dptpgmm | [9] | Online tp-gmm learning and lqr-based trajectory generation |
-| demo_glsl | [8] | Rendering example with glsl display |
-| demo_glsl_gfx | [8] | Rendering example with glsl display (using glfx) |
 | demo_LQR_infHor | [1] | Discrete infinite horizon linear quadratic regulation |
 | demo_MPC_batch_01 | [1,8] | Model predictive control (MPC) with batch linear quadratic tracking (LQT) formulation |
 | demo_MPC_iterative_01 | [1,8] | Model predictive control (MPC) with iterative linear quadratic tracking (LQT) formulation |
@@ -208,7 +197,4 @@ This project will build a number of executables, as listed in the table below.
 | demo_Riemannian_cov_interp02 | [4] | Covariance interpolation on Riemannian manifold from a GMM with augmented covariances |
 | demo_Riemannian_quat_infHorLQR | [3] | Linear quadratic regulation on hypersphere (orientation as unit quaternions) by relying on Riemannian manifold and infinite-horizon LQR |
 | demo_Riemannian_sphere_infHorLQR | [3] | Linear quadratic regulation on a sphere by relying on Riemannian manifold and infinite-horizon LQR |
-| demo_teleop | [7] | Online learning of tp-hsmm model and teleoperator-like usage example |
-| demo_tp_multiLqr | [7] | Online tp-hsmm and tp-gmm with lqr-based trajectory generation and multiframe-lqr trajectory generation |
-| demo_tp_trajMpc | [7] | Online tp-hsmm learning and trajMPC-based trajectory generation when communication is cut |