A Highest order hypothesis compatibility test for monocular SLAM
Cita com:
hdl:2117/20473
Tipus de documentArticle
Data publicació2013-08
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Simultaneous Location and Mapping (SLAM) is a
key problem to solve in order to build truly autonomous mobile robots. SLAM with a unique camera, or monocular SLAM, is probably one of the most complex SLAM variants, based entirely on a bearing-only sensor working over six DOF. The monocular SLAM method developed in this work is based on the Delayed Inverse-Depth (DI-D) Feature
Initialization, with the contribution of a new data association batch validation technique, the Highest Order Hypothesis
Compatibility Test, HOHCT.
The Delayed Inverse-Depth technique is used to initialize new features in the system and
defines a single hypothesis for the initial depth of features with the use of a stochastic technique of triangulation. The
introduced HOHCT method is based on the evaluation of statistically compatible hypotheses and a search algorithm
designed to exploit the strengths of the Delayed Inverse-Depth technique to achieve good performance results. This work presents the HOHCT with a detailed formulation of
the monocular DI-D SLAM problem. The performance of the proposed HOHCT is validated with experimental results, in both in door and outdoor environments, while its
costs are compared with other popular approaches.
CitacióGuerra, E. [et al.]. A Highest order hypothesis compatibility test for monocular SLAM. "International journal of advanced robotic systems", Agost 2013, vol. 10, núm. 311, p. 1-11.
ISSN1729-8806
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