AutoRef system architecture: Difference between revisions

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The system architecture for the [[AutoRef - Autonomous Referee System|AutoRef]] autonomous referee for [https://msl.robocup.org/ RoboCup Middle Size League (MSL)] robot soccer is a proposed conceptual model which describes the structure, behavior, and more views of the AutoRef system[https://en.wikipedia.org/wiki/Systems_architecture#cite_note-1 REFERENCE LIST NEEDED].
The system architecture for the [[AutoRef - Autonomous Referee System|AutoRef]] autonomous referee for [https://msl.robocup.org/ RoboCup Middle Size League (MSL)] robot soccer is a proposed conceptual model which describes the structure, behavior, and more views of the AutoRef system.


[[AutoRef MSD 2020]] primarily focused on specifying the functions of the AutoRef as derived from the [https://msl.robocup.org/rules MSL rulebook (v21.4)]. In short, this ''functional specification'' is a breakdown of MSL rule (or ''law'') into robot ''skills'' through robot ''tasks'': tasks are statements describing what the AutoRef must do to enforce the rules, written in plain language as to fully explain referee actions without describing the means by which to achieve them; skills are fundamental abilities which are needed to accomplish a specific task.
[[AutoRef MSD 2020]] primarily focused on specifying the functions of the AutoRef as derived from the [https://msl.robocup.org/rules MSL rulebook (v21.4)]. In short, this ''functional specification'' is a breakdown of MSL rule (or ''law'') into robot ''skills'' through robot ''tasks'': tasks are statements describing what the AutoRef must do to enforce the rules, written in plain language as to fully explain referee actions without describing the means by which to achieve them; skills are fundamental abilities which are needed to accomplish a specific task.

Revision as of 11:17, 31 March 2021

The system architecture for the AutoRef autonomous referee for RoboCup Middle Size League (MSL) robot soccer is a proposed conceptual model which describes the structure, behavior, and more views of the AutoRef system.

AutoRef MSD 2020 primarily focused on specifying the functions of the AutoRef as derived from the MSL rulebook (v21.4). In short, this functional specification is a breakdown of MSL rule (or law) into robot skills through robot tasks: tasks are statements describing what the AutoRef must do to enforce the rules, written in plain language as to fully explain referee actions without describing the means by which to achieve them; skills are fundamental abilities which are needed to accomplish a specific task.

A systems thinking approach underscores the system architecture.

Recommendations for future work emphasize an updated functional decomposition to synchronize the textual breakdown of law-task-skill and the corresponding game state flow visualization.

Systems thinking

Stakeholder concerns

An analysis of concerns for the AutoRef system led to the definition of two key concerns: continuity and fairness.

Continuity

Concern for continuity in AutoRef's development was particularly a stepping point for the system architecture's development.

Archive team of MSD 2020 concluded continuity was not emphasized or achieved [better word choice] by previous team contributions to AutoRef. The archive team's analysis justified/proved stakeholders concern regarding continuity.

This archiving concluded that this continuity was not achieved partly due to:

  • unclear global overarching structure
  • lack of an overview across previous team contributions

Outcome

The archiving process's result that a clearly defined global overarching structure was missing combined with the systems thinking's analysis of stakeholder concerns (for continuity) led to the conclusion that the translation of laws in the MSL rulebook into ...

Law-task-skill

Decided to translate rulebook from laws to tasks and break them down into skills.

Why? Referee must enforce rules — primary function/duty of a referee.

Functional decomposition

Law-task-skill breakdown (database)

Game state flow visualization