LLMが構築する階層木による異種マルチロボットチームの汎用ミッション計画
Generalized Mission Planning for Heterogeneous Multi-Robot Teams via LLM-constructed Hierarchical Trees
LLMと専用APIで階層木を構築し、各ロボットの制約と能力に合わせて複雑なミッションを分解・スケジューリングする異種マルチロボットチームの計画手法を提案した。
著者: Piyush Gupta, David Isele, Enna Sachdeva, Pin-Hao Huang, Behzad Dariush, Kwonjoon Lee, Sangjae Bae
分類: cs.RO, cs.AI, cs.MA
原文アブストラクト
We present a novel mission-planning strategy for heterogeneous multi-robot teams, taking into account the specific constraints and capabilities of each robot. Our approach employs hierarchical trees to systematically break down complex missions into manageable sub-tasks. We develop specialized APIs and tools, which are utilized by Large Language Models (LLMs) to efficiently construct these hierarchical trees. Once the hierarchical tree is generated, it is further decomposed to create optimized schedules for each robot, ensuring adherence to their individual constraints and capabilities. We demonstrate the effectiveness of our framework through detailed examples covering a wide range of missions, showcasing its flexibility and scalability.
