位置推定不確かさ下でのEMに基づくマルチロボット自律探索と地図構築
Multi-Robot Autonomous Exploration and Mapping Under Localization Uncertainty with Expectation-Maximization
分散型マルチロボットチーム向けに、地図と自己位置の不確かさを考慮した自律探索アルゴリズムを提案し、EM風の反復手法で次行動を評価して地図不確かさの抑制と効率的なタスク配分を両立させた。
著者: Yewei Huang, Xi Lin, Brendan Englot
分類: cs.RO
原文アブストラクト
We propose an autonomous exploration algorithm designed for decentralized multi-robot teams, which takes into account map and localization uncertainties of range-sensing mobile robots. Virtual landmarks are used to quantify the combined impact of process noise and sensor noise on map uncertainty. Additionally, we employ an iterative expectation-maximization inspired algorithm to assess the potential outcomes of both a local robot's and its neighbors' next-step actions. To evaluate the effectiveness of our framework, we conduct a comparative analysis with state-of-the-art algorithms. The results of our experiments show the proposed algorithm's capacity to strike a balance between curbing map uncertainty and achieving efficient task allocation among robots.
