Sensor influence in the performance of simultaneous mobile robot localization and map building

Castellanos, José A.; Montiel, José María; Neira, José; Tardós, Juan D.

doi:10.1007/bfb0119407

Cited by 34 publications

(17 citation statements)

References 9 publications

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“…Existing vision-based approaches use low-level features such as vertical edges (Castellanos et al 1999) and have complex data association problems. Our approach uses high-level image features which are scale invariant, thus greatly facilitating feature correspondence.…”

Section: Literature Reviewmentioning

confidence: 99%

Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks

Se¹,

Lowe

Little

2002

The International Journal of Robotics Research

546

185

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Section: Literature Reviewmentioning

confidence: 99%

Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks

Se¹,

Lowe

Little

2002

The International Journal of Robotics Research

546

185

View full text Add to dashboard Cite

show abstract

“…In principle, this form of navigation clinches the concept of a fully autonomous vehicle. There have been substantial efforts in developing the SLAM algorithm for land, indoor and underwater vehicles (Castellanos et al 1999;Clark and Dissanayake 1999;Dissanayake et al 1999;Leonard and Durrant-Whyte 1991;Leonard, Carpenter, and Feder 1999;Rencken 1993;Thrun, Burgard, and Fox 2000;Thrun et al 2002;Williams et al 2000) with excellent results. There are two SLAM related goals in this project:…”

Section: Introductionmentioning

confidence: 94%

The ANSER Project: Data Fusion across Multiple Uninhabited Air Vehicles

Sukkarieh¹,

Nettleton

Kim

et al. 2003

int j robot res

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The objective of the autonomous navigation and sensing experiment research (ANSER) project is to demonstrate decentralized data fusion (DDF) and simultaneous localization and map building (SLAM) across multiple uninhabited air vehicles (UAVs). To achieve this objective, the project specifies the development of four UAVs, where each UAV houses up to two terrain sensors and an INS/GPS navigation system. The terrain sensors include a scanning radar, laser/vision and standard vision system. The DDF concept has to be shown to be effective both on a single UAV and on multiple UAVs. The proof of the concept will lie in the ability of the DDF structure to conduct multi-target tracking problems as well as SLAM. To obtain this goal, a number of subgoals are required, most of which have never been attempted before on a research level. The objective of this paper is to present these goals as an overview of the ANSER project along with some simulated and real-time results.

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“…Davison and Murray (1998) implemented a real-time system where a 3D map of visual template landmarks was build and observed using fixating stereo vision. Castellanos et al (1994) built a 2D SLAM system combining straight segments from monocular vision and odometry, and trinocular straight segments and odometry. Davison (2003) demonstrated 3D SLAM using monocular vision as the only sensor, also using a smooth motion model for the camera to take the place of odometry this system exhibited unprecedented demonstrable real time performance for general indoors scenes observed with a low cost hand-held camera.…”

Section: Slammentioning

confidence: 99%

Drift-Free Real-Time Sequential Mosaicing

et al. 2008

Self Cite

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We present a sequential mosaicing algorithm for a calibrated rotating camera which can for the first time build drift-free, consistent spherical mosaics in real-time, automatically and seamlessly even when previously viewed parts of the scene are re-visited. Our mosaic is composed of elastic triangular tiles attached to a backbone map of feature directions over the unit sphere built using a sequential EKF SLAM (Extend Kalman Filter Simultaneous Localization And Mapping) approach.This method represents a significant advance on previous mosaicing techniques which either require off-line optimization or which work in real-time but use local alignment of nearby images and ultimately drift. We demonstrate the system's real-time performance with real-time mosaicing results from sequences with 360 degrees pan. The system shows good global mosaicing ability despite the challenging conditions: hand-held simple low-resolution webcam, varying natural outdoor illumination, and people moving in the scene.

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Sensor influence in the performance of simultaneous mobile robot localization and map building

Cited by 34 publications

References 9 publications

Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks

Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks

The ANSER Project: Data Fusion across Multiple Uninhabited Air Vehicles

Drift-Free Real-Time Sequential Mosaicing

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