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== Acknowledgments ==
The development of KnowRob has partly been funded by the DFG excellence initiative research cluster [[http://www.cotesys.org|Cognition for Technical Systems (CoTeSys)]] and the EU FP7 projects [[https://roboearth.org|RoboEarth]] and [[https://robohow.eu|RoboHow]].


Only released in EOL distros:  

knowrob: bosch_semantic_map | comp_cop | comp_germandeli | comp_orgprinciples | comp_spatial | comp_temporal | ias_knowledge_base | ias_prolog_addons | ias_semantic_map | jpl | json_prolog | knowrob_actions | knowrob_cad_parser | knowrob_common | knowrob_objects | knowrob_omics | mod_probcog | mod_srdl | mod_vis | rosprolog | semweb | srldb | tf_prolog | thea

Package Summary

KnowRob is a knowledge processing framework developed in the IAS group at the Technische Universitaet Muenchen, Germany. It provides tools for knowledge acquisition, representation and reasoning that are tailored to the demands in mobile robotics.

knowrob: comp_cop | comp_orgprinciples | comp_semantic_map | comp_spatial | comp_temporal | ias_knowledge_base | ias_prolog_addons | ias_semantic_map | jpl | json_prolog | knowrob_actions | knowrob_cad_parser | knowrob_common | knowrob_objects | knowrob_omics | mod_probcog | mod_srdl | mod_vis | rosprolog | semweb | srldb | tf_prolog | thea

Package Summary

KnowRob is a knowledge processing framework for robots. It has originally been developed in the IAS group at Technische Universitaet Muenchen, Germany and is currently maintained by Moritz Tenorth at the Institute for Artificial Intelligence in Bremen, Germany. It provides tools for knowledge acquisition, representation and reasoning that are tailored to the demands in mobile robotics.

knowrob: comp_cop | comp_orgprinciples | comp_semantic_map | comp_spatial | comp_temporal | ias_knowledge_base | ias_prolog_addons | ias_semantic_map | jpl | json_prolog | json_prolog_msgs | knowrob_actions | knowrob_cad_parser | knowrob_common | knowrob_objects | knowrob_omics | mod_probcog | mod_srdl | mod_vis | rosprolog | semweb | srldb | tf_prolog | thea

Package Summary

KnowRob is a knowledge processing framework for robots. It has originally been developed in the IAS group at Technische Universitaet Muenchen, Germany and is currently maintained by Moritz Tenorth at the Institute for Artificial Intelligence in Bremen, Germany. It provides tools for knowledge acquisition, representation and reasoning that are tailored to the demands in mobile robotics.

Installation

Besides common ROS stacks, the knowrob stack depends on the stack ias_common. To install it, check out the following two repositories:

git clone http://code.in.tum.de/git/ias-common.git ias_common
svn co http://code.in.tum.de/pubsvn/knowrob/tags/latest knowrob

Both stacks are also available as deb packages.

News

Documentation and Package List

  • Starting and accessing Prolog
    • rosprolog: Start an interactive Prolog shell

    • json_prolog: Start ROS service that offers a query interface

  • Base system
    • ias_knowledge_base: Core ontology and basic reasoning modules

    • knowrob_common: Common utilities for handling OWL (import/export, OWL reasoner interface, convenience query predicates), units of measure, and other generic functionality

    • knowrob_objects: Object-related functionality, supporting spatio-temporal reasoning, generation of the internal object representation, representation and conversion of coordinates

    • knowrob_actions: Read action properties, project effects of actions and processes, reason about transformations of objects induced by actions

    • ias_semantic_map: Semantic environment map representation in OWL

    • ias_prolog_addons: Prolog extensions such as the interface to the Weka and Mallet classification libraries, Jython interface, computation of semantic similarity measures between concepts

    • semweb: Semantic Web library of SWI prolog with extensions, e.g. computable properties

    • thea: OWL parser library

  • Reasoning packages
    • comp_spatial: Compute qualitative spatial relations from object poses

    • comp_temporal: Compute temporal relations, e.g. Allen's interval algebra

    • mod_vis: Visualization of the content of the knowledge base

    • knowrob_cad_models: Load Collada models for visualization and reasoning

    • mod_srdl: Description of robot components and capabilities and methods for matching these descriptions against requirements of actions

    • mod_probcog: Interface to the ProbCog statistical relational learning library

  • Interfaces to perception components
  • Probabilistic reasoning
  • Related packages:
    • comp_ehow: Import of natural-language web instructions, removed from KnowRob to reduce dependencies

Some further documentation can be found here: http://ias.in.tum.de/kb/wiki/

Tutorials

A longer KnowRob tutorial was part of the CoTeSys ROS Fall School in November 2010 in Munich. The lecture material and example code can be found at http://www.ros.org/wiki/Events/CoTeSys-ROS-School/Day5 . The example code may be slightly outdated though.

More tutorials can be found in the KnowRob wiki:

White papers

The following pages provide some introduction into conceptual aspects and the way different things are modeled in the system.

Publications

Currently, the most comprehensive overview of the KnowRob system and related research can be found in Moritz Tenorth's PhD thesis. The full list of KnowRob-related publications is available at https://ias.in.tum.de/research/knowledge

When you publish a paper using KnowRob, please cite the original paper at IROS 2009

@InProceedings{tenorth09knowledge,
  author  = {Moritz Tenorth and Michael Beetz},
  title = {{KnowRob -- Knowledge Processing for Autonomous Personal Robots}},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={4261--4266},
  year = {2009}
}

Acknowledgments

The development of KnowRob has partly been funded by the DFG excellence initiative research cluster Cognition for Technical Systems (CoTeSys) and the EU FP7 projects RoboEarth and RoboHow.

Wiki: knowrob (last edited 2014-12-08 09:21:54 by MoritzTenorth)