AIエージェントとマルチLMMモジュールによる移動建設ロボットの即興タスク対応位置決め
Task-Aware Positioning for Improvisational Tasks in Mobile Construction Robots via an AI Agent with Multi-LMM Modules
建設現場の即興タスクに対応するため、自然言語指示を理解し、図面から位置を特定して移動するAIエージェントを四足ロボットで実装し、92.2%の成功率を達成した。
著者: Seongju Jang, Francis Baek, SangHyun Lee
分類: cs.RO
原文アブストラクト
Due to the ever-changing nature of construction, many tasks on sites occur in an improvisational manner. Existing mobile construction robot studies remain limited in addressing improvisational tasks, where task-required locations, timing of task occurrence, and contextual information required for task execution are not known in advance. We propose an agent that understands improvisational tasks given in natural language, identifies the task-required location, and positions itself. The agent's functionality was decomposed into three Large Multimodal Model (LMM) modules operating in parallel, enabling the application of LMMs for task interpretation and breakdown, construction drawing-based navigation, and visual reasoning to identify non-predefined task-required locations. The agent was implemented with a quadruped robot and achieved a 92.2% success rate for identifying and positioning at task-required locations across three tests designed to assess improvisational task handling. This study enables mobile construction robots to perform non-predefined tasks autonomously.