並列連続時間相対自己位置推定のための拡張クランプ非一様Bスプライン
Parallel Continuous-Time Relative Localization with Augmented Clamped Non-Uniform B-Splines
複数ロボットの非同期計測に対応するため、クランプ非一様Bスプラインで状態を表現し、スライディングウィンドウ最適化をロボットごとに並列化した連続時間相対慣性オドメトリ手法を提案。
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著者: Jiadong Lu, Zhehan Li, Tao Han, Miao Xu, Chao Xu, Yanjun Cao
分類: cs.RO
原文アブストラクト
Accurate relative localization is critical for multi-robot cooperation. In robot swarms, measurements from different robots arrive asynchronously and with clock time-offsets. Although Continuous-Time (CT) formulations have proved effective for handling asynchronous measurements in single-robot SLAM and calibration, extending CT methods to multi-robot settings faces great challenges to achieve high-accuracy, low-latency, and high-frequency performance. Especially, existing CT methods suffer from the inherent query-time delay of unclamped B-splines and high computational cost. This paper proposes CT-RIO, a novel Continuous-Time Relative-Inertial Odometry framework. We employ Clamped Non-Uniform B-splines (C-NUBS) to represent robot states for the first time, eliminating the query-time delay. We further augment C-NUBS with closed-form extension and shrinkage operations that preserve the spline shape, making it suitable for online estimation and enabling flexible knot management. This flexibility leads to the concept of knot-keyknot strategy, which supports spline extension at high-frequency while retaining sparse keyknots for adaptive relative-motion modeling. We then formulate a sliding-window relative localization problem that operates purely on relative kinematics and inter-robot constraints. To meet the demanding computation required at swarm scale, we decompose the tightly-coupled optimization into robot-wise sub-problems and solve them in parallel using incremental asynchronous block coordinate descent. Extensive experiments show that CT-RIO converges from time-offsets as large as 263 ms to sub-millisecond within 3 s, and achieves RMSEs of 0.046 m and 1.8 {\deg}. It consistently outperforms state-of-the-art methods, with improvements of up to 60% under high-speed motion.
