Semantic World#
Welcome to the semantic world package! The semantic world is a python package that unifies the access and manipulation of scene graphs. It features a:
Unified API to scene graphs
Forward simulation for worlds and agents
Semantic interpretation of structures in the world
Automatic serialization of worlds to databases
Connecting worlds to different simulator backends through Multiverse [GN24]
This package originates from different developments of the AICOR Institute for Artificial Intelligence. Four different projects developed a very similar component for different parts of cognitive modules. This project aims to unify it under one solution that is flexible enough for all the different applications.
World#
The central datastructure for interaction with a scene is the semantic_world.world_entity.World.
The world is a mediator for bodies and their connections.
It handles the validation of the world’s kinematic structure and the communication between the objects.
Physical Objects can be spawned by constructing a semantic_world.world_entity.Body and a kinematic chain of
those elements is added by specifying a semantic_world.world_entity.Connection between bodies.
All those things have to be added to the world for full functionality. More information on the kinematic world model can be found here.
WorldReasoner#
The world reasoner semantic_world.reasoner.WorldReasoner is a class that uses Ripple Down Rules
to classify concepts and attributes of the world. This is done using a rule based classifier that benefits from incremental
rule addition through querying the system and answering the prompts that pop up using python code.
The benefit of that is the rules of the reasoner are based on the world datastructures and are updates as the datastructures are updated. Thus, the rules become a part of the semantic world repository and are update, migrated, and versioned with it.
More information about the world reasoner can be found here.
Views#
A View (semantic_world.world_entity.View) is a different representation for a part or a collection of parts in the world that has a semantic meaning and
functional purpose in specific contexts.
For example, a Drawer can be seen as a view on a handle and a container that is connected via a fixed connection and where the container has some prismatic connection.
Views can be inferred by specifying rules that make up a view. More information on how the views are inferred and used can be found here.
Database#
The entire world can be saved to any database
that has an sqlalchemy connector.
The definitions and relationships for the database are automatically derived from the datastructures
derived in the python package via the ormatic package.
The types for sqlalchemy are defined in semantic_world.orm.model.
The interface to sqlalchemy is auto-generated to semantic_world.orm.ormatic_interface.
The script to recreate the interface is found in here.
Learn more about the ORM in this tutorial.