部分観測下でのラベル付きマルチベルヌーイフィルタを用いた通信不要の分散マルチロボットタスク割り当て
Communication-Free Distributed Multi-Robot Task Allocation under Partial Observations Using Labeled Multi-Bernoulli Filtering
各ロボットがLMBフィルタで近傍ロボットの位置を推定し、欲張りオークション方式でタスクを割り当てることで、明示的な通信なしに分散協調を実現する手法を提案した。
著者: Takumi Ito, Akiya Kamimura
分類: cs.RO, eess.SY
原文アブストラクト
This paper proposes a communication-free multi-robot task allocation framework based solely on local observations. In this study, tasks are defined as reaching target locations. Each robot estimates the positions of neighboring robots using a Labeled Multi-Bernoulli (LMB) filter and independently assigns tasks through a greedy auction-based strategy. By continuously updating state estimates and reallocating tasks during execution, the proposed method enables decentralized coordination without explicit communication. Monte Carlo simulations demonstrate that the proposed method enables effective cooperative task allocation without inter-robot communication while remaining robust to measurement clutter and observation uncertainty.