Discover tu-rbo/concarne Open Source project by RBO (@tu-rbo)

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MIT License
Created almost 9 years ago
Updated over 8 years ago

tu-rbo

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Lightweight framework for learning with side information (aka privileged information), based on Theano and Lasagne. For more info on learning with side information see http://arxiv.org/abs/1511.06429

differentiable-particle-filters

Source code and data for the paper "Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors"

Python

177

turbo-ros-pkg

ROS software repository, Robotics & Biology Laboratory, TU Berlin

C++

omip

Framework for Online Interactive Perception (OMIP) for robots and system to perceive kinematic structures of articulated objects from interactions. For more info on the framework and the system see http://www.robotics.tu-berlin.de/fileadmin/fg170/Publikationen_pdf/martinmartin_ip_iros_2014.pdf

C++

learning-state-representations-with-robotic-priors

Code and data accompaning the paper "Learning State Representations with Robotic Priors" (Jonschkowski and Brock, 2015).

Python

hybrid-automaton-library

Library for creating feedback-based motion descriptions for robots.

C++

articulated-objects

The RBO Dataset of Articulated Objects and Interactions

Python

omip_msgs

Supplementary package that defines the messages for OMIP (Online Multimodal Interactive Perception)

CMake

tu-rbo/concarne

tu-rbo

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