UWB SLAM with Rao-Blackwellized Monte Carlo data association

Deißler, Tobias; Thielecke, Jörn

doi:10.1109/ipin.2010.5647596

Cited by 35 publications

(22 citation statements)

References 8 publications

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“…The results are used to verify the theoretical work in [2]. Also, they provide important performance considerations for localization schemes making use of multipath propagation, like [6] or [7], for example. Fig.…”

Section: Introductionmentioning

confidence: 84%

Analysis of position-related information in measured UWB indoor channels

Meißner

Witrisal

2012

2012 6th European Conference on Antennas and Propagation (EUCAP)

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Conventional radio-based indoor localization systems often only make use of the direct signal path between an agent and the anchor nodes. Therefore, performance can deteriorate in non-line-of-sight situations, even though reflected multipath-components carry useful location-dependent information. Using ultra-wideband signals, these components become resolvable. Bringing together previously obtained results on the Cramér-Rao bound on the position error and measurement data along a reference trajectory, we present a methodology for quantifying the position-related information contained in UWB indoor channels. An explicit model for the diffuse part of the channel enables to evaluate its importance realistically. Experimental results verify prior theoretical work. Important parameters and their influence on the system performance are discussed.

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Section: Introductionmentioning

confidence: 84%

Analysis of position-related information in measured UWB indoor channels

Meißner

Witrisal

2012

2012 6th European Conference on Antennas and Propagation (EUCAP)

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“…Deissler et al [16] presented a SLAM algorithm based on a ultra-wideband (UWB) radar with a bat-type antenna array. This algorithm was developed for catastrophic scenarios, where the environment is corrupted with smoke or dust.…”

Section: Related Workmentioning

confidence: 99%

“…The biggest challenge is data association, i.e. assigning the time of flight of a given measurement from the radar to the corresponding landmark [16]. The authors solved this situation by using a RBPF for the data association process and an Extended Kalman Filter to estimate the state vector.…”

Section: Related Workmentioning

confidence: 99%

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A Sensor Fusion Layer to Cope with Reduced Visibility in SLAM

Santos

Couceiro

Portugal

et al. 2015

J Intell Robot Syst

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Mapping and navigating with mobile robots in scenarios with reduced visibility, e.g. due to smoke, dust, or fog, is still a big challenge nowadays. In spite of the tremendous advance on Simultaneous Localization and Mapping (SLAM) techniques for the past decade, most of current algorithms fail in those environments because they usually rely on optical sensors providing dense range data, e.g. laser range finders, stereo vision, LIDARs, RGB-D, etc., whose measurement process is highly disturbed by particles of smoke, dust, or steam. This article addresses the problem of performing SLAM under reduced visibility conditions by proposing a sensor fusion layer which takes advantage from complementary characteristics between a laser range finder (LRF) and an array of sonars. This sensor fusion layer is ultimately used with a state-of-the-art SLAM technique to be resilient in scenarios where visibility cannot be assumed at all times. Special attention is given to mapping using commercial off-the-shelf (COTS) sensors, namely arrays of sonars which, being usually available in robotic platforms, raise technical issues that were investigated in the course of this work. Two sensor fusion methods, a heuristic method and a fuzzy logic-based method, are presented and discussed, corresponding to different stages of the research work conducted. The experimental validation of both methods with two different mobile robot platforms in smoky indoor scenarios showed that they provide a robust solution, using only COTS sensors, for adequately coping with reduced visibility in the SLAM process, thus decreasing significantly its impact in the mapping and localization results obtained.

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“…Its solution requires novel tracking algorithms accounting for the geometry at hand, online channel analysis for extracting deterministic MPCs, and data association for mapping MPCs to hypothesized signal sources. It bears similarity to the simultaneous localization and mapping (SLAM) problem [4]- [6]. However, we have to deal with a signal source that typically has no angle resolution 1 and is heavily affected by diffuse multipath, which makes the feature detection and data association much more challenging.…”

Section: Introductionmentioning

confidence: 99%

Performance bounds for multipath-assisted indoor navigation and tracking (MINT)

Witrisal

Meißner

2012

2012 IEEE International Conference on Communications (ICC)

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The MINT (multipath-assisted indoor navigation and tracking) problem exploits the geometry of deterministic multipath components (MPCs) for robust indoor positioning in line-of-sight (LOS) and non-LOS situations. It assumes a known room layout and can thus easily make use of signals reflected by the walls, for instance. In this paper, the Cramér-Rao lower bound of the positioning error is derived for this problem. This requires a novel channel model, where diffuse multipath is modeled as a colored Gaussian process that influences the effective SNR of deterministic MPCs. The adverse effect of path overlap is demonstrated and discussed. Computational results show the three-fold importance of a large signal bandwidth. The bandwidth reciprocal (i.e. the pulse duration) multiplies the error standard deviation-a fundamental result well-known from AWGN channels. But it also multiplies the effective power of the interfering diffuse multipath and gives rise to additional path overlap. A minimum bandwidth of 1 GHz seems appropriate and sufficient.

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UWB SLAM with Rao-Blackwellized Monte Carlo data association

Cited by 35 publications

References 8 publications

Analysis of position-related information in measured UWB indoor channels

Analysis of position-related information in measured UWB indoor channels

A Sensor Fusion Layer to Cope with Reduced Visibility in SLAM

Performance bounds for multipath-assisted indoor navigation and tracking (MINT)

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