Calibrating the kinematic parameters of a mobile platform is a time consuming and mandatory procedure, since the mechanical tolerances and the assembly procedures may introduce a large inaccuracy in the nominal parameters. A small error in the calibration might lead to severe inconsistencies in tasks that rely on sensor information such as localization, mapping and navigation in general. In this paper we focus on the so called kinematic calibration. In a wheeled mobile platform this consists of estimating the odometry parameters, that are required to convert wheel encoder ticks in a relative motion of the mobile base on a local plane. We propose the use of the unscented Kalman filter for estimating the geometrical kinematic parameters of a mobile platform, using an external tracking sensor. The method can either be used online, to identify parameters and monitor their value while the system is operating, or offline, on logged data. We validate this method on a 4 mecanum-wheel mobile platform using a camera to track the movement trough a reference chessboard.

UKF vision based mobile platform kinematic parameters calibration

Mutti S;Pedrocchi N
2021

Abstract

Calibrating the kinematic parameters of a mobile platform is a time consuming and mandatory procedure, since the mechanical tolerances and the assembly procedures may introduce a large inaccuracy in the nominal parameters. A small error in the calibration might lead to severe inconsistencies in tasks that rely on sensor information such as localization, mapping and navigation in general. In this paper we focus on the so called kinematic calibration. In a wheeled mobile platform this consists of estimating the odometry parameters, that are required to convert wheel encoder ticks in a relative motion of the mobile base on a local plane. We propose the use of the unscented Kalman filter for estimating the geometrical kinematic parameters of a mobile platform, using an external tracking sensor. The method can either be used online, to identify parameters and monitor their value while the system is operating, or offline, on logged data. We validate this method on a 4 mecanum-wheel mobile platform using a camera to track the movement trough a reference chessboard.
2021
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
9781510644052
Mobile robot calibration
UKF
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/429389
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