Mobile Robot Localization from Large-Scale Appearance Mosaics

Kelly, Alonzo

doi:10.1177/02783640022067896

Cited by 39 publications

(19 citation statements)

References 47 publications

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“…This constitutes a drawback as the representation is not fit for human perception, which is important for mission definition. Recently, Kelly [20] has addressed the feasibility and implementation issues of using large mosaics for robot guidance, predicting a large impact of these techniques on industrial environments. In this case, the problem is simplified by assuming that the image plane is parallel to the mosaiced areas and the motion of the vehicles is restricted to the ground plane.…”

Section: ) Mosaic Construction With Global Registrationmentioning

confidence: 99%

Mosaic-based navigation for autonomous underwater vehicles

Gracias

Zwaan

Bernardino

et al. 2003

IEEE J. Oceanic Eng.

129

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Abstract-We propose an approach for vision-based navigation of underwater robots that relies on the use video mosaics of the sea bottom as environmental representations for navigation.We present a methodology for building high quality video mosaics of the sea bottom, in a fully automatic manner, that ensures global spatial coherency. During navigation, a set of efficient visual routines are used for the fast and accurate localization of the underwater vehicle with respect to the mosaic. These visual routines were developed taking into account the operating requirements of real-time position sensing, error bounding and computational load.A visual servoing controller, based on the vehicle kinematics, is used to drive the vehicle along a computed trajectory, specified in the mosaic, while maintaining constant altitude. The trajectory towards a goal point is generated online to avoid undefined areas in the mosaic.We have conducted a large set of sea trials, under realistic operating conditions. This paper demonstrates that, without resorting to additional sensors, visual information can be used to create environment representations of the sea bottom (mosaics) and support long runs of navigation in a robust manner.

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Section: ) Mosaic Construction With Global Registrationmentioning

confidence: 99%

Mosaic-based navigation for autonomous underwater vehicles

Gracias

Zwaan

Bernardino

et al. 2003

IEEE J. Oceanic Eng.

129

View full text Add to dashboard Cite

show abstract

“…Such algorithms have been used, for instance, for autonomous heading control for obstacle avoidance for fixed-wing aircraft [21], estimating distance to the ground and canyon walls from unmanned aerial vehicles [6], and autonomous landing for helicopters [17]. In the odometry realm, downward-facing cameras have been successfully used for positioning in pre-explored environments by correlating the visible area against an existing database [8], however such methods are inapplicable to planetary rovers observing most patches for the first time.…”

Section: Introductionmentioning

confidence: 99%

Outdoor Downward-Facing Optical Flow Odometry with Commodity Sensors

Dille

Grocholsky

Singh

2010

Springer Tracts in Advanced Robotics

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Positioning is a key task in most field robotics applications but can be very challenging in GPS-denied or high-slip environments. A common tactic in such cases is to position visually, and we present a visual odometry implementation with the unusual reliance on optical mouse sensors to report vehicle velocity. Using multiple kilometers of data from a lunar rover prototype, we demonstrate that, in conjunction with a moderate-grade inertial measurement unit, such a sensor can provide an integrated pose stream that is at times more accurate than that achievable by wheel odometry and visibly more desirable for perception purposes than that provided by a high-end GPS-INS system. A discussion of the sensor's limitations and several drift mitigating strategies attempted are presented.

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“…Similarly Kröse and Bunschoten [4] acquire additional images by rotating in place, in order distinguish positions with similar appearance. Kelly [11] composes extended image sequences into globally consistent mosaics and then tracks motion over the mosaic to estimate the current pose. Matsumoto et al [12] navigate in a sequence of images, assuming that the robot makes transitions in order from one memorized image to the next.…”

Section: Introductionmentioning

confidence: 99%

Topological Mapping with Multiple Visual Manifolds

Grudić¹,

Mulligan²

2005

Robotics: Science and Systems I

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Abstract-We address the problem of building topological maps in visual space for robot navigation. The nodes of our topological maps consist of clusters along manifolds, and we propose an unsupervised learning algorithm that automatically constructs these manifolds -the user need only specify the desired number of clusters and the minimum number of images per cluster. This spectral clustering like framework allows each cluster to optimize a separate set of clustering parameters, and we demonstrate empirically that this flexibility can significantly improve clustering results. We further propose a framework for servoing the robot in our manifold space, which would allow the robot to navigate from any point on one manifold (topological node) to any specified point on a second manifold. Finally, we present experimental results on indoor and outdoor image sequences demonstrating the efficacy of the proposed algorithm.

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Mobile Robot Localization from Large-Scale Appearance Mosaics

Cited by 39 publications

References 47 publications

Mosaic-based navigation for autonomous underwater vehicles

Mosaic-based navigation for autonomous underwater vehicles

Outdoor Downward-Facing Optical Flow Odometry with Commodity Sensors

Topological Mapping with Multiple Visual Manifolds

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