diff --git a/README.md b/README.md index bd90197cfffb513a7d747f90d06d710c1704f298..30e8464a9db9970facdfad487f5ca451b11d63dc 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,28 @@ -# 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 |