Pinned Repositories
ADHSMM
The MATLAB codes show simple examples for trajectory generation and control of a robot manipulator, which are built on an adaptive duration hidden semi-Markov model (ADHSMM). The models, algorithms and results given in these codes are part of a project aimed at learning proactive and reactive collaborative robot behaviors.
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
CollaborativeTransportation2D
The MATLAB code shows a simple collaborative transportation task carried out on a planar workspace. The models, algorithms and results given in this code are linked to the T-RO paper "Learning Physical Robot Collaborative Behaviors from Human Demonstrations"
dmr
Topic Models with Dirichlet-multinomial Regression
drake
A planning, control, and analysis toolbox for nonlinear dynamical systems. Please see the WIKI for documentation.
ManipulabilityTracking
ManipulabilityTransfer
MATLAB example code of manipulability transfer approach using GMM/GMR over SPD manifold
pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
pyrobolearn
PyRoboLearn: a Python framework for Robot Learning
pyrobolearn
PyRoboLearn: a Python framework for Robot Learning
lrozo's Repositories
lrozo/ADHSMM
The MATLAB codes show simple examples for trajectory generation and control of a robot manipulator, which are built on an adaptive duration hidden semi-Markov model (ADHSMM). The models, algorithms and results given in these codes are part of a project aimed at learning proactive and reactive collaborative robot behaviors.
lrozo/CollaborativeTransportation2D
The MATLAB code shows a simple collaborative transportation task carried out on a planar workspace. The models, algorithms and results given in this code are linked to the T-RO paper "Learning Physical Robot Collaborative Behaviors from Human Demonstrations"
lrozo/ManipulabilityTransfer
MATLAB example code of manipulability transfer approach using GMM/GMR over SPD manifold
lrozo/ManipulabilityTracking
lrozo/pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
lrozo/pyrobolearn
PyRoboLearn: a Python framework for Robot Learning
lrozo/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
lrozo/dmr
Topic Models with Dirichlet-multinomial Regression
lrozo/drake
A planning, control, and analysis toolbox for nonlinear dynamical systems. Please see the WIKI for documentation.
lrozo/geomloss
Geometric loss functions between point clouds, images and volumes
lrozo/geomstats
Computations and statistics on manifolds with geometric structures.
lrozo/geoopt
Riemannian Adaptive Optimization Methods with pytorch optim
lrozo/GPmat
Matlab implementations of Gaussian processes and other machine learning tools.
lrozo/GPyOpt
Gaussian Process Optimization using GPy
lrozo/hyperbolic-learning
Implemented ML algorithms in hyperbolic geometry (MDS, K-Means, Support vector machines, etc.)
lrozo/libbarrett
Communication and controls library for Barrett products
lrozo/lorentz_embeddings_recreation
A recreation of the Lorentz embeddings paper from ICML 2018 (Nickel 2018)
lrozo/mushroom-rl
Python library for Reinforcement Learning experiments.
lrozo/optimaltransport
Optimal transport transforms
lrozo/optimaltransport.github.io
Web site of the Computational Optimal Transport book
lrozo/osim-rl
Reinforcement learning environments with musculoskeletal models
lrozo/poincare-embeddings
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
lrozo/POT
Python Optimal Transport library
lrozo/PythonRobotics
Python sample codes for robotics algorithms.
lrozo/robotics-toolbox-python
Robotics Toolbox for Python
lrozo/SafeOpt
Safe Bayesian Optimization
lrozo/sedumi
SeDuMi: A linear/quadratic/semidefinite solver for Matlab and Octave
lrozo/swgmm
Sliced Wasserstein Distance for Learning Gaussian Mixture Models
lrozo/tensorforce
TensorForce: A TensorFlow library for applied reinforcement learning