AutoRef MSD 2020

Note: Team-specific pages (such as this one) are for explaining a team's contribution to the overall AutoRef project. Team-specific pages from MSD 2020 onwards do not describe the technical details of the AutoRef system. If you are documenting AutoRef items as a member of MSD 2020 or any other future project, please add details to the general AutoRef page and/or the respective system architecture or implementation pages.

MSD 2020 logo

See AutoRef for an overview of the autonomous referee system, including past work and current system architecture and implementation.

AutoRef MSD 2020 (formally AutoRef PDEng MSD 2020 or simply MSD 2020) was a team contribution to the development of AutoRef, an autonomous referee for RoboCop Middle Size League (MSL) robot soccer. It was completed by the 2020–2022 cohort of Mechatronic System Design (MSD) PDEng trainees at Eindhoven University of Technology (TU/e) from February–March 2021 for their Block II in-house project.

Contributions by the MSD 2020 team include establishing a system architecture for AutoRef based on a functional specification of the referee enforcement domain and implementing ball-player distance violation detection technology. The team also contributed to the reemphasis of continuity in AutoRef's development, including an updated approach to how AutoRef is documented — namely, in the AutoRef wiki pages.

MSD 2020's contributions mark a paradigm shift in team contributions to AutoRef's development history. The team eliminated the requirement of quadcopter drones as the basis for the autonomous refereeing system and reemphasized continuity as a key stakeholder concern. The functional specification developed by MSD 2020 as a law-task-skill breakdown for the system architecture likewise signifies a shift in AutoRef's development, whereby fundamental skills are to be combined to achieve refereeing tasks to enforce MSL rules.

Background

In February 2021 the MSD 2020 team was given two tasks for their PDEng program's Block II in-house project:

1. archive past AutoRef PDEng work (i.e., MSD 2015–2019); and
2. develop the AutoRef with continuity in mind.

These tasks were requested by two stakeholders, Erjen Lefeber and René van de Molengraft, representing both academic and technological interests for AutoRef.

The only technical specification provided by these stakeholders was for AutoRef to be an autonomous refereeing system for RoboCup Middle Size League (MSL) as to fully replace human refereeing in MSL. Lefeber provided hardware from the MSD 2019 team which included (among other items) two Crazy Flie drones. MSD 2020 was asked to; however, no specification

In other words, MSD 2020 was not required to use any particular technology or hardware.

Objectives and scope

• Overhauled the wiki for AutoRef

System architecture

See AutoRef system architecture for full technical details.

Contributions to AutoRef's system architecture in AutoRef MSD 2020 primarily focused on specifying the functions of the autonomous referee for RoboCop Middle Size League 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.

Before reaching functional specification, MSD 2020 applied a systems thinking approach to AutoRef. The team also recommends future work.

Functional decomposition

The intent, approach, and realization of the functional specification...

Implementation

See AutoRef implementation for full technical details.

Contributions to AutoRef's implementation in AutoRef MSD 2020 primarily involved detecting ball-to-player distance violations.

Team

The contributions towards AutoRef explained on this page were completed by the 2020–2022 cohort of Mechatronic System Design (MSD) PDEng trainees at Eindhoven University of Technology (TU/e) — namely:

• Anand Vazhayil Surendran
• Aneesh Ashok Kumar
• Gijs Linskens
• Haoyu Zhu
• Ivan Kolodko
• Lars Maxfield
• Mahmoud Abdelhady
• Maryam Mashayekhi