灯台と大域グラフ安定化：低計算資源・狭視野ロボットのための能動SLAM
Lighthouses and Global Graph Stabilization: Active SLAM for Low-compute, Narrow-FoV Robots
視野が狭く計算資源が限られたロボット向けに、情報量の多いパノラマ視点「灯台」を活用して局所地図を安定化し、さらに大域的な姿勢グラフを安定化する能動SLAM探索戦略を提案し、実環境で評価した。
著者: Mohit Deshpande, Richard Kim, Dhruva Kumar, Jong Jin Park, Jim Zamiska
分類: cs.RO
原文アブストラクト
Autonomous exploration to build a map of an unknown environment is a fundamental robotics problem. However, the quality of the map directly influences the quality of subsequent robot operation. Instability in a simultaneous localization and mapping (SLAM) system can lead to poorquality maps and subsequent navigation failures during or after exploration. This becomes particularly noticeable in consumer robotics, where compute budget and limited field-of-view are very common. In this work, we propose (i) the concept of lighthouses: panoramic views with high visual information content that can be used to maintain the stability of the map locally in their neighborhoods and (ii) the final stabilization strategy for global pose graph stabilization. We call our novel exploration strategy SLAM-aware exploration (SAE) and evaluate its performance on real-world home environments.
