可観測性を考慮した軌道最適化：理論・実現可能性・最新動向
Observability-Aware Trajectory Optimization: Theory, Viability, and State of the Art
可観測性に基づく軌道最適化の代表的手法2つを比較し、理論的整理と物理シミュレータでの自己校正実験を通じて有効性と限界を検証した論文。
著者: Christopher Grebe, Emmett Wise, Jonathan Kelly
分類: cs.RO
原文アブストラクト
Ideally, robots should move in ways that maximize the knowledge gained about the state of both their internal system and the external operating environment. Trajectory design is a challenging problem that has been investigated from a variety of perspectives, ranging from information-theoretic analyses to leaning-based approaches. Recently, observability-based metrics have been proposed to find trajectories that enable rapid and accurate state and parameter estimation. The viability and efficacy of these methods is not yet well understood in the literature. In this paper, we compare two state-of-the-art methods for observability-aware trajectory optimization and seek to add important theoretical clarifications and valuable discussion about their overall effectiveness. For evaluation, we examine the representative task of sensor-to-sensor extrinsic self-calibration using a realistic physics simulator. We also study the sensitivity of these algorithms to changes in the information content of the exteroceptive sensor measurements.
