ConFusion：非線形最適化による複雑なロボットシステムのためのセンサフュージョン
ConFusion: Sensor Fusion for Complex Robotic Systems using Nonlinear Optimization
移動ホライズン推定器で異種センサの計測を融合するオープンソースのモジュール型フレームワークを提案し、視覚慣性追跡と移動マニピュレータの全身センサフュージョンで有効性を示した。
著者: Timothy Sandy, Lukas Stadelmann, Simon Kerscher, Jonas Buchli
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
We present ConFusion, an open-source package for online sensor fusion for robotic applications. ConFusion is a modular framework for fusing measurements from many heterogeneous sensors within a moving horizon estimator. ConFusion offers greater flexibility in sensor fusion problem design than filtering-based systems and the ability to scale the online estimate quality with the available computing power. We demonstrate its performance in comparison to an iterated extended Kalman filter in visual-inertial tracking, and show its versatility through whole-body sensor fusion on a mobile manipulator.
