Zobrazeno 1 - 10
of 27
pro vyhledávání: '"John Mullane"'
Publikováno v:
IEEE Robotics & Automation Magazine. 21:26-37
Having been referred to as the Holy Grail of autonomous robotics research, simultaneous localization and mapping (SLAM) lies at the core of most the autonomous robotic applications [1]. This article explains the recent advances in the representations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e18a175faccc1a46b341e18e61913b36
https://doi.org/10.1109/mra.2014.2304111
https://doi.org/10.1109/mra.2014.2304111
Publikováno v:
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
Artículos CONICYT
CONICYT Chile
instacron:CONICYT
Artículos CONICYT
CONICYT Chile
instacron:CONICYT
In autonomous applications, a vehicle requires reliable estimates of its location and information about the world around it. To capture prior knowledge of the uncertainties in a vehicle's motion response to input commands and sensor measurements, thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4921fc6431842cca405fc869bd3c40e9
https://doi.org/10.1109/mits.2013.2260596
https://doi.org/10.1109/mits.2013.2260596
Publikováno v:
IEEE Transactions on Robotics. 27:268-282
This paper proposes an integrated Bayesian frame work for feature-based simultaneous localization and map building (SLAM) in the general case of uncertain feature number and data association. By modeling the measurements and feature map as random fin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56a3a1155b3a1f1ef207c2b548266fb0
https://doi.org/10.1109/tro.2010.2101370
https://doi.org/10.1109/tro.2010.2101370
Publikováno v:
IEEE Sensors Journal. 10:960-971
Millimeter Wave (MMW) radars are currently used as range measuring devices in applications such as automotive driving aids (Langer and Jochem, 1996), (Rohling and Mende, 1996), the mapping of mines (Brooker et al., 2005) and autonomous field robotics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f5356ca249d58eab893f5265c3e2593
https://doi.org/10.1109/jsen.2009.2037013
https://doi.org/10.1109/jsen.2009.2037013
Publikováno v:
The International Journal of Robotics Research. 28:172-190
The classical occupancy grid formulation requires the use of a priori known measurement likelihoods whose values are typically either assumed or learned from training data. Furthermore, in previous approaches, the likelihoods used to propagate the oc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6422449d9457ec66c88405dfb4823073
https://doi.org/10.1177/0278364908097214
https://doi.org/10.1177/0278364908097214
Publikováno v:
Robotics and Autonomous Systems. 55:72-85
Range measuring sensors can play an extremely important role in robot navigation. All range measuring devices rely on a ‘detection criterion’ made in the presence of noise, to determine when the transmitted signal is considered detected and hence
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3adea1937ff1e70eafc7d078dd0ba427
https://doi.org/10.1016/j.robot.2006.06.010
https://doi.org/10.1016/j.robot.2006.06.010
Publikováno v:
ARSO
This paper presents a Gaussian Particle Filter based solution to the Simultaneous Localization and Mapping problem. Conventional SLAM algorithms estimate the map and the vehicle trajectory using either an Extended Kalman Filter (EKF), or a combinatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::283ff9fd980019f0c830c1e404998059
https://doi.org/10.1109/arso.2013.6705515
https://doi.org/10.1109/arso.2013.6705515
Publikováno v:
OCEANS 2011 IEEE - Spain.
This paper presents an alternative formulation for the Factorised Solution to the Simultaneous Localization and Mapping (FastSLAM) algorithm using an Adaptive Extended Kalman Filter based approach. The FastSLAM algorithm jointly estimates the pose of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3031dd6ebc609d5f13ab2b021f60434b
https://doi.org/10.1109/oceans-spain.2011.6003630
https://doi.org/10.1109/oceans-spain.2011.6003630
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783642213892
We begin the justification for the use of RFSs by re-evaluating the basic issues of feature representation, and considering the fundamental mathematical relationship between environmental feature representations, and robot motion. We further the just
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e38cff37a1e36c2ce885f6ec61b254b
https://doi.org/10.1007/978-3-642-21390-8_2
https://doi.org/10.1007/978-3-642-21390-8_2
Publikováno v:
Springer Tracts in Advanced Robotics ISBN: 9783642213892
The previous chapter provided the motivation to adopt an RFS representation for the map in both FBRM and SLAM problems. The main advantage of the RFS formulation is that the dimensions of the measurement likelihood and the predicted FBRM or SLAM stat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cabc9004b64158acda8b1238a15f66a9
https://doi.org/10.1007/978-3-642-21390-8_3
https://doi.org/10.1007/978-3-642-21390-8_3