Simultaneous localization and mapping: part I

Sensor-based simultaneous localization and mapping - Part I: GAS robocentric filter

This paper presents the design, analysis, and experimental validation of a sensor-based globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM) with application to uninhabited aerial vehicles (UAVs). The SLAM problem is first formulated in a sensor-based framework, without any type of vehicle pose information, and modified in such a way that the underlying s...

Simultaneous Localization and Mapping

Simultaneous Localization and Mapping

The last few years have seen the implementation of autonomous systems in industrial applications that operate in a reliable and consistent manner in areas such as stevedoring, mining, agriculture and a variety of indoor applications. To solve the localisation problem, these systems make use of either absolute information such as GPS, beacons at known positions or available maps of the environme...

Simultaneous Localization and Mapping

In the event of an emergency due to a fire or other crisis, a necessary but time consuming pre-requisite, that could delay the real rescue operation, is to establish whether the ground or area can be entered safely by human emergency workers. The objective of the VIEWFINDER research project is to develop robots which have the primary task of gathering data. The robots are equipped with sensors ...

Simultaneous Localization and Mapping

Detection and tracking of moving objects (DATMO) in crowded urban areas from a ground vehicle at high speeds is difficult because of a wide variety of targets and uncertain pose estimation from odometry and GPS/DGPS. In this paper we present a solution of the simultaneous localization and mapping (SLAM) with DATMO problem to accomplish this task using ladar sensors and odometry. With a precise ...