mlsanityData to 14 Oct 2026

Play Everywhere: A Temporal Logic based Game Environment Independent Approach for Playing Soccer with Robots

arXiv 2405.12628 ↗First posted 21 May 2024cs.RO cs.AIcited by 2

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Abstract (arXiv)

Robots playing soccer often rely on hard-coded behaviors that struggle to generalize when the game environment change. In this paper, we propose a temporal logic based approach that allows robots' behaviors and goals to adapt to the semantics of the environment. In particular, we present a hierarchical representation of soccer in which the robot selects the level of operation based on the perceived semantic characteristics of the environment, thus modifying dynamically the set of rules and goals to apply. The proposed approach enables the robot to operate in unstructured environments, just as it happens when humans go from soccer played on an official field to soccer played on a street. Three different use cases set in different scenarios are presented to demonstrate the effectiveness of the proposed approach.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 12 references that are in the map. First posted on arXiv 21 May 2024.

Builds on

3 of 12 references.

References · 3

  1. 2019Google Research Football: A Novel Reinforcement Learning Environmentcited by 260
  2. 2022Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic: A Polynomial Reduction to Standard Planningcited by 2
  3. 2016A Proposal for Semantic Map Representation and Evaluationcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.