Repository of Executable Scenarios

This is the landing page for the Repository of Executable Scenarios, which consists of metamodels and models created during the development and application of tools in the Executable Workbench and ExSce Management to support the ExSce Concept and Methodology. In the following sections, we first present the different metamodels developed for ExSce, organized by their respective domains. Afterwards, we list the tutorials showcasing how these metamodels can be composed to create composable models and the various transformations enabled by our tools to support different use cases.

Metamodels

Geometry

Geometric concepts such as spatial relations, their coordinates or geometric shapes.

File	Description
coordinates.json	Coordinate representations associated with spatial relations such as position coordinate vectors or discrete cosine matrices
spatial-operators.json	Operators on spatial relations such as the composition of positions
spatial-relations.json	Spatial relations include positions (linear and angular) and their time derivatives (velocities and accelerations) but also directional (e.g. left/right or in front of) and distance relations (between different structural entities)
structural-entities.json	The most fundamental geometric entities and relations including points, vectors, frames or simplicial complices (the “skeleton” of a rigid body)
polytope.json	Concepts to model polytopes

Kinematic Chain

Kinematic chains are motion constraints between geometric entities

File	Description
operators.json	Operators on kinematic chains include maps between joint space and Cartesian space quantities (e.g. forward kinematics) but also projections that occur in dynamics solvers
state.json	Simple joints can have constrained, lower-dimensional representations of the joint’s motion state which includes joint positions, velocities and accelerations
structural-entities.json	Structural entities of kinematic chains are all about joints that constrain the relative motion between geometric entities

Algorithm

According to Merriam-Webster, an algorithm can be broadly defined as “a step-by-step procedure for solving a problem or achieving a desired outcome.” When it comes to Multi-Robot Systems (MRS), our focus lies in computational problems that are pertinent to implementing various MRS behaviors.

File	Description
algorithm.json	Metamodel to specify the computations necessary for MRS to achieve the goals. (TODO link to longer documentation).

Dynamics

TODO

File	Description
newtonian-rigid-body-dynamics.json	TODO

Physical Quantities and Units

Any robot model must conform to physical quantities and units because a robotic system acts in the physical world

File	Description
qudt.json	QUDT is an established ontology of physical quantities and units, here we just represent the JSON-LD context

Acceptance Criteria

Metamodels for specifying acceptance criteria of robotic scenarios.

File	Description
bdd.json	Metamodel for specifying BDD templates and their variants, see documentation
agent.json	Metamodel for specifying agents in a robotic scenario, see documentation
environment.json	Metamodel for specifying elements in the environment of a robotic scenario, see documentation
task.json	Metamodel for specifying task-related concepts and relations in a robotic scenario, see documentation

Coordination

Metamodels for coordinating the execution of robot behaviours

File	Description
event.json	Metamodel for specifying event-driven coordination of robot behaviours, see documentation

Floor Plan

Metamodels for specifying indoor environments and objects

File	Description
floor-plan.json	Concepts for modelling floor plans
object.json	Concepts for modelling objects
state.json	Concepts for modelling states

Simulation

Metamodels for specific simulators

File	Description
gazebo.json	Concepts for modelling the visual and collision representation of objects for Gazebo

Tutorials

The development of tools in the ExSce Workbench produces many artefacts, either as compositions of our metamodels or from various transformations to support different use cases. Finding a single structure to organize these artefacts can therefore be challenging, since they often involve the complex interplay of different domains and support different stakeholder activities. As such, we present our models through a list of tutorials showcasing how they can be composed and transformed to serve specific stakeholder workflows. The tutorials can then link to our models while describing how they are used in the context of each workflow. Many of our models are hosted on the hbrs-sesame/models repository, for which a landing page is also available. Our tutorials include:

Modelling and Generating Gherkin features for A Simple Pickup task

Executable Scenario