A Simultaneous Localization and Mapping(SLAM) system is a complex program consisting of several interconnected components with different functionalities such as optimization, tracking or loop detection. Whereas the literature addresses in detail how enhancing the algorithmic aspects ofthe individual components improves SLAM performance, the modal aspects, such as when to localize, relocalize or close a loop, are usually left aside. In this paper, we address the modal aspects of a SLAM system and show that the design of the modal controller has a strong impact on SLAM performance in particular in terms of robustness against unforeseen events such as sensor failures, perceptual aliasing or kidnapping. We preset a novel taxonomy for the components of a modern SLAM system, investigate their interplay and propose a highly modular architecture of a generic SLAM system using the Unified Modeling LanguageTM(UML) state machine formalism. The result, called SLAM state machine, is compared to the modal controller of several state-of-the-art SLAM systems and evaluated in two experiments. We demonstrate that our state machine handles unforeseen events much more robustly than the state-of-the-art systems.

Better Lost in Transition Than Lost in Space: SLAM State Machine / Colosi, Mirco; Haug, Sebastian; Biber, Peter; Arras, Kai O.; Grisetti, Giorgio. - (2019), pp. 362-369. (Intervento presentato al convegno 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) tenutosi a Macau; China) [10.1109/IROS40897.2019.8968182].

Better Lost in Transition Than Lost in Space: SLAM State Machine

Colosi, Mirco
Primo
;
Grisetti, Giorgio
2019

Abstract

A Simultaneous Localization and Mapping(SLAM) system is a complex program consisting of several interconnected components with different functionalities such as optimization, tracking or loop detection. Whereas the literature addresses in detail how enhancing the algorithmic aspects ofthe individual components improves SLAM performance, the modal aspects, such as when to localize, relocalize or close a loop, are usually left aside. In this paper, we address the modal aspects of a SLAM system and show that the design of the modal controller has a strong impact on SLAM performance in particular in terms of robustness against unforeseen events such as sensor failures, perceptual aliasing or kidnapping. We preset a novel taxonomy for the components of a modern SLAM system, investigate their interplay and propose a highly modular architecture of a generic SLAM system using the Unified Modeling LanguageTM(UML) state machine formalism. The result, called SLAM state machine, is compared to the modal controller of several state-of-the-art SLAM systems and evaluated in two experiments. We demonstrate that our state machine handles unforeseen events much more robustly than the state-of-the-art systems.
2019
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
SLAM; State machine; SLAM architecture; Simultaneous Localization and Mapping;
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Better Lost in Transition Than Lost in Space: SLAM State Machine / Colosi, Mirco; Haug, Sebastian; Biber, Peter; Arras, Kai O.; Grisetti, Giorgio. - (2019), pp. 362-369. (Intervento presentato al convegno 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) tenutosi a Macau; China) [10.1109/IROS40897.2019.8968182].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1358704
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