異種計測群の統合協調位置推定：統一データ駆動手法
Integrated cooperative localization of heterogeneous measurement swarm: A unified data-driven method
異なる計測能力を持つロボット群の協調位置推定問題に対し、相互計測とオドメトリのみを用いたペア相対位置推定と、弱連結な有向計測トポロジー下での分散協調位置推定を実現する統一データ駆動手法を提案した。
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著者: Kunrui Ze, Wei Wang, Guibin Sun, Jiaqi Yan, Kexin Liu, Jinhu Lü
分類: cs.RO
原文アブストラクト
The cooperative localization (CL) problem in heterogeneous robotic systems with different measurement capabilities is investigated in this work. In practice, heterogeneous sensors lead to directed and sparse measurement topologies, whereas most existing CL approaches rely on multilateral localization with restrictive multi-neighbor geometric requirements. To overcome this limitation, we enable pairwise relative localization (RL) between neighboring robots using only mutual measurement and odometry information. A unified data-driven adaptive RL estimator is first developed to handle heterogeneous and unidirectional measurements. Based on the convergent RL estimates, a distributed pose-coupling CL strategy is then designed, which guarantees CL under a weakly connected directed measurement topology, representing the least restrictive condition among existing results. The proposed method is independent of specific control tasks and is validated through a formation control application and real-world experiments.
