In this paper, robots equipped with two complementary typologies of redundant sensors are considered: one typology provides sharp measures of some geometrical entity related to the robot pose (e.g., distance or angle) but is not univocally associated with this quantity; the other typology is univocal but is characterized by a low level of precision. A technique is proposed to properly combine these two kinds of measurement both in a stochastic and in a deterministic context. This framework may occur in robotics, for example, when the distance from a known landmark is detected by two different sensors, one based on the signal strength or time of flight of the signal, while the other one measures the phase-shift of the signal, which has a sharp but periodical dependence on the robot-landmark distance. In the stochastic case, an effective solution is a two-stage extended Kalman filter (EKF) which exploits the precise periodic signal only when the estimate of the robot position is sufficiently precise. In the deterministic setting, an approach based on a switching hybrid observer is proposed, and results are analyzed via simulation examples.

Carnevale, D., & Martinelli, F. (2015). State estimation for robots with complementary redundant sensors. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 12 [10.5772/60528].

State estimation for robots with complementary redundant sensors

CARNEVALE, DANIELE;MARTINELLI, FRANCESCO
2015-10

Abstract

In this paper, robots equipped with two complementary typologies of redundant sensors are considered: one typology provides sharp measures of some geometrical entity related to the robot pose (e.g., distance or angle) but is not univocally associated with this quantity; the other typology is univocal but is characterized by a low level of precision. A technique is proposed to properly combine these two kinds of measurement both in a stochastic and in a deterministic context. This framework may occur in robotics, for example, when the distance from a known landmark is detected by two different sensors, one based on the signal strength or time of flight of the signal, while the other one measures the phase-shift of the signal, which has a sharp but periodical dependence on the robot-landmark distance. In the stochastic case, an effective solution is a two-stage extended Kalman filter (EKF) which exploits the precise periodic signal only when the estimate of the robot position is sufficiently precise. In the deterministic setting, an approach based on a switching hybrid observer is proposed, and results are analyzed via simulation examples.
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/04 - Automatica
English
Con Impact Factor ISI
Redundant Sensors, Kalman Filtering, Robot Localization, Observer for Nonlinear Systems
Article Number: 138
Carnevale, D., & Martinelli, F. (2015). State estimation for robots with complementary redundant sensors. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 12 [10.5772/60528].
Carnevale, D; Martinelli, F
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/186913
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