System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma, Tao Wu, Yiyang Song, Haoxuan Ru, Yifan Zhong, Ruilin Yan, Lingfeng Li, Ruochong Li, Yu Li, Xuyuan Han, Yun Ding, Ruizhang Jiang, Xiaochuan Zhang, Yichao Li, Yuanpei Chen, Yaodong Yang, Yitao Liang

TL;DR
This paper presents a system architecture for maintaining internal state consistency in long-horizon robotic tabletop games, focusing on Mahjong, through explicit state management, monitoring, and recovery mechanisms to improve reliability.
Contribution
It introduces an integrated system design that explicitly maintains and monitors internal state, incorporating verified action primitives and recovery strategies for long-horizon robotic games.
Findings
Explicit state partitioning improves reliability.
Monitoring detects turn violations and hidden info breaches.
Recovery mechanisms mitigate error propagation.
Abstract
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-making modules, and ultimately derail interaction. This paper studies how to maintain internal state consistency in turn-based, multi-human robotic tabletop games through deliberate system design rather than isolated component improvement. Using Mahjong as a representative long-horizon setting, we present an integrated architecture that explicitly maintains perceptual, execution, and interaction state, partitions high-level semantic reasoning from time-critical perception and control, and incorporates verified action primitives with tactile-triggered recovery to prevent premature state corruption. We further introduce interaction-level monitoring mechanisms to detect turn violations and hidden-information…
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Taxonomy
TopicsAdvanced Software Engineering Methodologies · Real-Time Systems Scheduling · Formal Methods in Verification
