A Call for Deeper Collaboration Between Robotics and Game Development

While robotics and game development have independently achieved significant progress in creating interactive and intelligent systems, a deeper collaboration between these fields could be mutually beneficial. This paper argues for more collaboration, highlighting current limited interactions and proposing directions for future research. We discuss shared foundations such as Artificial Intelligence, Extended Reality, and the increasing use of common tools and standards. We then propose opportunities where game development methodologies can advance robotics (e.g., gamified data collection and richer simulation environments) and where robotics research can contribute to games (e.g., improved NPC autonomy and embodied intelligence). This cross-disciplinary interaction can accelerate innovation and lead to more intelligent and usercentered technologies in both domains.

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Publication Details

Published
2025-08-19
DOI
https://doi.org/10.1109/cog64752.2025.11114209
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
0.00

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A Call for Deeper Collaboration Between Robotics and Game Development

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A Call for Deeper Collaboration Between Robotics and Game Development

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article en

Abstract

While robotics and game development have independently achieved significant progress in creating interactive and intelligent systems, a deeper collaboration between these fields could be mutually beneficial. This paper argues for more collaboration, highlighting current limited interactions and proposing directions for future research. We discuss shared foundations such as Artificial Intelligence, Extended Reality, and the increasing use of common tools and standards. We then propose opportunities where game development methodologies can advance robotics (e.g., gamified data collection and richer simulation environments) and where robotics research can contribute to games (e.g., improved NPC autonomy and embodied intelligence). This cross-disciplinary interaction can accelerate innovation and lead to more intelligent and usercentered technologies in both domains.

KTH Royal Institute of Technology (SE)
Stiftelsen för Strategisk Forskning, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet
Openalex Percentile: Top 89%
Reinforcement Learning in Robotics
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