Decentralized Behavior Tree-Based Multi-AMR Transportation in LNG Carrier Cargo Tanks

Document Type

Article

Publication Date

1-1-2026

Abstract

This paper presents a decentralized multi-autonomous mobile robot (AMR) system for automating Top Bridge Pad (TBP) transportation inside liquefied natural gas (LNG) carrier cargo tanks, where confined spaces, shared transport routes, process-dependent work locations, and limited communication infrastructure constrain conventional material-transport systems. The proposed system employs four-wheel-steering AMRs integrating LiDAR-based localization, path planning, landmark-based workspace detection, and motion control. For multi-robot operation, each AMR locally executes a behavior tree (BT) while exchanging its task state, position, travel direction, and mission progress with the peer robot. The coordination framework integrates task-state-aware priority determination, costmap-based shelter-point generation, and task-state-preserving interruption and resumption, enabling an AMR to temporarily leave a shared route and subsequently resume its interrupted transportation or return sequence. Physical experiments using two AMRs verified workspace entry, yielding, shelter-point-based collision avoidance, and task resumption under representative shared-route interaction scenarios. Repeated continuous-operation experiments further confirmed that the proposed framework maintained transportation continuity and successfully resolved the encountered conflict and avoidance situations during multi-AMR operation. These results demonstrate the functional feasibility and practical operating capability of the proposed framework for process-specific material transportation in confined industrial environments.

Publication Title

IEEE Access

Link to Full Text

Share

COinS