Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers

Newman, Paul; Sibley, Gabe; Smith, Mike; Cummins, Mark; Harrison, Alastair; Mei, Christopher; Posner, Ingmar; Shade, Robbie; Schroeter, Derik; Murphy, Liz; Churchill, Winston; Cole, Dave; Reid, Ian

doi:10.1177/0278364909341483

Cited by 123 publications

(84 citation statements)

References 51 publications

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“…Data were gathered from a two wheeled Segway RMP~200 platform with two vertically aligned SICK LMS291-S14 laser sensors mounted on the side of the vehicle. Pose estimates were obtained using visual odometry from a forward facing stereoscopic camera [13]. Throughout we use the Matérn class of covariance functions, a length scale l of 8, a process variance σ 2 p of 0.05m and a active window size of 200, all of which were found empirically Figure 5.…”

Section: Resultsmentioning

confidence: 99%

Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data

Smith

Posner

Newman

2010

Robotics: Science and Systems VI

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Abstract-This paper concerns the creation of efficient surface representations from laser point clouds. We produce a continuous, implicit, non-parametric representation with an update time that is constant. The algorithm places no restriction on the complexity of the underlying workspace surfaces and automatically prunes redundant data via an information theoretic criterion. This criterion makes the use of Gaussian Process regression a natural choice. We adopt a formulation which handles the typical non-functional relation between XY-location and elevation allowing us to map arbitrary environments. Results are presented that use real and synthetic data to analyse the trade-off between compression level and reconstruction error. We attain decimation factors in excess of two orders of magnitude without significant degradation in fidelity.

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Section: Resultsmentioning

confidence: 99%

Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data

Smith

Posner

Newman

2010

Robotics: Science and Systems VI

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“…The FAB-MAP implement openFABMAP [31], which produces results comparable to those presented in [2]. Parame FAB-MAP were taken from for CAT-SLAM on the same dataset are College, Oxford, pictured in Fig.…”

Section: B Algorithm Parametersmentioning

confidence: 93%

“…Appearance based methods are popular as a method of detecting loop closure in range based metric maps [1,2], and also for generating complete topological maps that can be used for path planning and navigation [3]. Appearance may refer more broadly to a robot's sensor signatures [4], but most often refers to a snapshot image of a location from a camera mounted on the robot.…”

Section: Introductionmentioning

confidence: 99%

Towards Persistent Localization and Mapping with a Continuous Appearance-based Topology

Maddern¹,

Milford²,

Wyeth³

2012

Robotics: Science and Systems VIII

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Abstract-Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearancebased localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

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“…It can also be thought of as a pre-processing step for ICP. Since these more standard versions of ICP are often used in ground robotics systems [17], [20], the proposed module, used as an alternative or complementary method for alignment, can have an impact on a variety of robotics platforms.…”

Section: Introductionmentioning

confidence: 99%

Scan segments matching for pairwise 3D alignment

Douillard

Quadros

Morton

et al. 2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-This paper presents a method for pairwise 3D alignment which solves data association by matching scan segments across scans. Generating accurate segment associations allows to run a modified version of the Iterative Closest Point (ICP) algorithm where the search for point-to-point correspondences is constrained to associated segments. The novelty of the proposed approach is in the segment matching process which takes into account the proximity of segments, their shape, and the consistency of their relative locations in each scan. Scan segmentation is here assumed to be given (recent studies provide various alternatives [10], [19]). The method is tested on seven sequences of Velodyne scans acquired in urban environments. Unlike various other standard versions of ICP, which fail to recover correct alignment when the displacement between scans increases, the proposed method is shown to be robust to displacements of several meters. In addition, it is shown to lead to savings in computational times which are potentially critical in real-time applications.

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Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers

Cited by 123 publications

References 51 publications

Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data

Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data

Towards Persistent Localization and Mapping with a Continuous Appearance-based Topology

Scan segments matching for pairwise 3D alignment

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