ConFusion: Sensor Fusion for Complex Robotic Systems Using Nonlinear Optimization

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 filter...

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Bibliographic Details
Published in:IEEE robotics and automation letters 2019-04, Vol.4 (2), p.1093-1100
Main Authors: Sandy, Timothy, Stadelmann, Lukas, Kerscher, Simon, Buchli, Jonas
Format: Article
Language:English
Subjects:
Confusion
Extended Kalman filter
Kalman filters
Measurement uncertainty
mobile manipulation
Nonlinear systems
Optimization
Robot sensing systems
Robotics
Sensor fusion
Sensors
Time measurement
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Summary: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 wholebody sensor fusion on a mobile manipulator.
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2019.2894168