Relevant bibliographies by topics / Simultaneous localisation and mapping

Academic literature on the topic 'Simultaneous localisation and mapping'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Simultaneous localisation and mapping"

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Kim, Jonghyuk. "Rao-Blackwellised Inertial Simultaneous Localisation and Mapping." IFAC Proceedings Volumes 41, no. 2 (2008): 9522–27. http://dx.doi.org/10.3182/20080706-5-kr-1001.01610.

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Wang, Xun, and JianGuo Wang. "Detecting glass in Simultaneous Localisation and Mapping." Robotics and Autonomous Systems 88 (February 2017): 97–103. http://dx.doi.org/10.1016/j.robot.2016.11.003.

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Wang, Sufang, Tingyang Xie, and Peng Chen. "Simultaneous localisation and mapping of intelligent mobile robots." International Journal of Cybernetics and Cyber-Physical Systems 1, no. 1 (2021): 93. http://dx.doi.org/10.1504/ijccps.2021.113103.

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Bryson, Mitch, and Salah Sukkarieh. "Architectures for Cooperative Airborne Simultaneous Localisation and Mapping." Journal of Intelligent and Robotic Systems 55, no. 4-5 (January 16, 2009): 267–97. http://dx.doi.org/10.1007/s10846-008-9303-9.

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Wang, Sufang, Tingyang Xie, and Peng Chen. "Simultaneous localisation and mapping of intelligent mobile robots." International Journal of Cybernetics and Cyber-Physical Systems 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijccps.2021.10033929.

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Ma, Teng, Ye Li, Yusen Gong, Rupeng Wang, Mingwei Sheng, and Qiang Zhang. "AUV Bathymetric Simultaneous Localisation and Mapping Using Graph Method." Journal of Navigation 72, no. 06 (July 5, 2019): 1602–22. http://dx.doi.org/10.1017/s0373463319000286.

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Although topographic mapping missions and geological surveys carried out by Autonomous Underwater Vehicles (AUVs) are becoming increasingly prevalent, the lack of precise navigation in these scenarios still limits their application. This paper deals with the problems of long-term underwater navigation for AUVs and provides new mapping techniques by developing a Bathymetric Simultaneous Localisation And Mapping (BSLAM) method based on graph SLAM technology. To considerably reduce the calculation cost, the trajectory of the AUV is divided into various submaps based on Differences of Normals (DoN). Loop closures between submaps are obtained by terrain matching; meanwhile, maximum likelihood terrain estimation is also introduced to build weak data association within the submap. Assisted by one weight voting method for loop closures, the global and local trajectory corrections work together to provide an accurate navigation solution for AUVs with weak data association and inaccurate loop closures. The viability, accuracy and real-time performance of the proposed algorithm are verified with data collected onboard, including an 8 km planned track recorded at a speed of 4 knots in Qingdao, China.
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Mahony, Robert, Tarek Hamel, and Jochen Trumpf. "An homogeneous space geometry for simultaneous localisation and mapping." Annual Reviews in Control 51 (2021): 254–67. http://dx.doi.org/10.1016/j.arcontrol.2021.04.012.

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van Goor, Pieter, Robert Mahony, Tarek Hamel, and Jochen Trumpf. "Constructive observer design for Visual Simultaneous Localisation and Mapping." Automatica 132 (October 2021): 109803. http://dx.doi.org/10.1016/j.automatica.2021.109803.

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Lepej, Peter, and Jurij Rakun. "Simultaneous localisation and mapping in a complex field environment." Biosystems Engineering 150 (October 2016): 160–69. http://dx.doi.org/10.1016/j.biosystemseng.2016.08.004.

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Bala, Jibril Abdullahi, Steve Adetunji Adeshina, and Abiodun Musa Aibinu. "Advances in Visual Simultaneous Localisation and Mapping Techniques for Autonomous Vehicles: A Review." Sensors 22, no. 22 (November 18, 2022): 8943. http://dx.doi.org/10.3390/s22228943.

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The recent advancements in Information and Communication Technology (ICT) as well as increasing demand for vehicular safety has led to significant progressions in Autonomous Vehicle (AV) technology. Perception and Localisation are major operations that determine the success of AV development and usage. Therefore, significant research has been carried out to provide AVs with the capabilities to not only sense and understand their surroundings efficiently, but also provide detailed information of the environment in the form of 3D maps. Visual Simultaneous Localisation and Mapping (V-SLAM) has been utilised to enable a vehicle understand its surroundings, map the environment, and identify its position within the area. This paper presents a detailed review of V-SLAM techniques implemented for AV perception and localisation. An overview of SLAM techniques is presented. In addition, an in-depth review is conducted to highlight various V-SLAM schemes, their strengths, and limitations. Challenges associated with V-SLAM deployment and future research directions are also provided in this paper.
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Dissertations / Theses on the topic "Simultaneous localisation and mapping"

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Eade, Ethan. "Monocular simultaneous localisation and mapping." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611415.

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Parsley, M. P. "Simultaneous localisation and mapping with prior information." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1318103/.

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This thesis is concerned with Simultaneous Localisation and Mapping (SLAM), a technique by which a platform can estimate its trajectory with greater accuracy than odometry alone, especially when the trajectory incorporates loops. We discuss some of the shortcomings of the "classical" SLAM approach (in particular EKF-SLAM), which assumes that no information is known about the environment a priori. We argue that in general this assumption is needlessly stringent; for most environments, such as cities some prior information is known. We introduce an initial Bayesian probabilistic framework which considers the world as a hierarchy of structures, and maps (such as those produced by SLAM systems) as consisting of features derived from them. Common underlying structure between features in maps allows one to express and thus exploit geometric relations between them to improve their estimates. We apply the framework to EKF-SLAM for the case of a vehicle equipped with a range-bearing sensor operating in an urban environment, building up a metric map of point features, and using a prior map consisting of line segments representing building footprints. We develop a novel method called the Dual Representation, which allows us to use information from the prior map to not only improve the SLAM estimate, but also reduce the severity of errors associated with the EKF. Using the Dual Representation, we investigate the effect of varying the accuracy of the prior map for the case where the underlying structures and thus relations between the SLAM map and prior map are known. We then generalise to the more realistic case, where there is "clutter" - features in the environment that do not relate with the prior map. This involves forming a hypothesis for whether a pair of features in the SLAMstate and prior map were derived from the same structure, and evaluating this based on a geometric likelihood model. Initially we try an incrementalMultiple Hypothesis SLAM(MHSLAM) approach to resolve hypotheses, developing a novel method called the Common State Filter (CSF) to reduce the exponential growth in computational complexity inherent in this approach. This allows us to use information from the prior map immediately, thus reducing linearisation and EKF errors. However we find that MHSLAM is still too inefficient, even with the CSF, so we use a strategy that delays applying relations until we can infer whether they apply; we defer applying information from structure hypotheses until their probability of holding exceeds a threshold. Using this method we investigate the effect of varying degrees of "clutter" on the performance of SLAM.
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Williams, Emily. "Simultaneous localisation and mapping for surveying applications." Thesis, University of Nottingham, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755820.

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Mobile Laser Scanning (MLS) is a data capture technique that has transformed the way in which survey data is collected especially for infrastructure corridors such as highways and railways. Using an integrated GPS and Inertial Measuring Unit (IMU), the mobile vehicle and therefore the collected data has a proven accuracy of +/- 10mm, when using ground control points. This allows high accuracy data collection at normal highway speeds. The main limitation of this type of data capture is the reliance on GPS for positioning. Although blackouts in GPS signal can be bridged using the IMU, the resulting error follows a time dependent model resulting in large errors after short periods of time. This prohibits the use of MLS for high accuracy applications in areas such as indoors and underground. Simultaneous Localisation and Mapping (SLAM) is a robotics technique that collects data about the environment as it navigates in order to make deeisionson its movement creating a completely autonomous robot. The main advantage of SLAM for mapping is that the robot does not rely on GPS to navigate its surroundings. Instead it relies wholly on relative measurements to the environment in which it travels. The maps created are a biproduct of the navigation solution and the accuracy of them is often overlooked. In order to use the maps created for purposes other than autonomy it is important that their creation is investigated and the final maps are critically assessed. This thesis is an investigation into using SLAM for the creation of high accuracy maps. Analysis is undertaken to assess the ability of these maps to be used for surveying applications. Initially an investigation is undertaken to understand the processes involved for the production of SLAM maps. With the primary outcome being to determine the perceived benefits of using the maps created using SLAM techniques for mobile mapping applications. Trials are undertaken to critically evaluate the capability of typical sensors used on board SLAM systems for the production of reliable measurements. The Zebedee system, developed by CSIRO is identified as a mapping tool which uses SLAM techniques. An error model is developed for this system using a traditional survey approach, the results of which are compared against data collected in an indoor and an underground environment. The resulting point clouds from the test sites are assessed to determine the surveying applications which this type of system can provide data for.
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Nemra, A. "Robust airborne 3D visual simultaneous localisation and mapping." Thesis, Cranfield University, 2011. http://dspace.lib.cranfield.ac.uk/handle/1826/6157.

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The aim of this thesis is to present robust solutions to technical problems of airborne three-dimensional (3D) Visual Simultaneous Localisation And Mapping (VSLAM). These solutions are developed based on a stereovision system available onboard Unmanned Aerial Vehicles (UAVs). The proposed airborne VSLAM enables unmanned aerial vehicles to construct a reliable map of an unknown environment and localise themselves within this map without any user intervention. Current research challenges related to Airborne VSLAM include the visual processing through invariant feature detectors/descriptors, efficient mapping of large environments and cooperative navigation and mapping of complex environments. Most of these challenges require scalable representations, robust data association algorithms, consistent estimation techniques, and fusion of different sensor modalities. To deal with these challenges, seven Chapters are presented in this thesis as follows: Chapter 1 introduces UAVs, definitions, current challenges and different applications. Next, in Chapter 2 we present the main sensors used by UAVs during navigation. Chapter 3 presents an important task for autonomous navigation which is UAV localisation. In this chapter, some robust and optimal approaches for data fusion are proposed with performance analysis. After that, UAV map building is presented in Chapter 4. This latter is divided into three parts. In the first part, a new imaging alternative technique is proposed to extract and match a suitable number of invariant features. The second part presents an image mosaicing algorithm followed by a super-resolution approach. In the third part, we propose a new feature detector and descriptor that is fast, robust and detect suitable number of features to solve the VSLAM problem. A complete Airborne Visual Simultaneous Localisation and Mapping (VSLAM) solution based on a stereovision system is presented in Chapter (5). Robust data association filters with consistency and observability analysis are presented in this chapter as well. The proposed algorithm is validated with loop closing detection and map management using experimental data. The airborne VSLAM is extended then to the multiple UAVs case in Chapter (6). This chapter presents two architectures of cooperation: a Centralised and a Decentralised. The former provides optimal precision in terms of UAV positions and constructed map while the latter is more suitable for real time and embedded system applications. Finally, conclusions and future works are presented in Chapter (7).
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Mountney, Peter Edward. "simultaneous localisation and mapping for minimally invasive surgery." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.530462.

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Williams, Brian P. "Simultaneous localisation and mapping using a single camera." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:2fccd8f6-170d-4c5b-b77b-7e371cad4df6.

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This thesis describes a system which is able to track the pose of a hand-held camera as it moves around a scene. The system builds a 3D map of point landmarks in the world while tracking the pose of the camera relative to this map using a process called simultaneous localisation and mapping (SLAM). To achieve real-time performance, the map must be kept sparse, but rather than observing only the mapped landmarks like previous systems, observations are made of features across the entire image. Their deviation from the predicted epipolar geometry is used to further constrain the estimated inter-frame motion and so improves the overall accuracy. The consistency of the estimation is also improved by performing the estimation in a camera-centred coordinate frame. As with any such system, tracking failure is inevitable due to occlusion or sudden motion of the camera. A relocalisation module is presented which monitors the SLAM system, detects tracking failure, and then resumes tracking as soon as the conditions have improved. This relocalisation process is achieved using a new landmark recognition algorithm which is trained on-line and provides high recall and a fast recognition time. The relocalisation module can also be used to achieve place recognition for a loop closure detection system. By taking into account both the geometry and appearance information when determining a loop closure this module is able to outperform previous loop closure detection techniques used in monocular SLAM. After recognising an overlap, the map is then corrected using a novel trajectory alignment technique that is able to cope with the inherent scale ambiguity in monocular SLAM. By incorporating all of these new techniques, the system presented can perform as a robust augmented reality system, or act as a navigation tool which could be used on a mobile robot in indoor and outdoor environments.
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Sinivaara, Kristian. "Simultaneous Localisation and Mapping using Autonomous Target Detection and Recognition." Thesis, Linköpings universitet, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110410.

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Simultaneous localisation and mapping (SLAM) is an often used positioning approach in GPS denied indoor environments. This thesis presents a novel method of combining SLAM with autonomous/aided target detection and recognition (ATD/R), which is beneficial for both methods. The method uses physical objects that are recognisable by ATR as unambiguous features in SLAM, while SLAM provides the ATR with better position estimates. The intended application is to improve the positioning of a first responder moving through an indoor environment, where the map offers localisation and simultaneously helps locate people, furniture and potentially dangerous objects like gas cannisters. The developed algorithm, dubbed ATR-SLAM, uses existing methods from different fields such as EKF-SLAM and ATR based on rectangle estimation. Landmarks in the form of 3D point features based on NARF are used in conjunction with identified objects and 3D object models are used to replace landmarks when the same information is used. This leads to a more compact map representation with fewer landmarks, which partly compensates for the introduced cost of the ATR. Experiments performed using point clouds generated from a time-of-flight laser scanner show that ATR-SLAM produces more consistent maps and more robust loop closures than EKF-SLAM using only NARF landmarks.
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Barkby, Stephen. "Efficient and Featureless Approaches to Bathymetric Simultaneous Localisation and Mapping." Thesis, The University of Sydney, 2011. http://hdl.handle.net/2123/7919.

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This thesis investigates efficient forms of Simultaneous Localization and Mapping (SLAM) that do not require explicit identification, tracking or association of map features. The specific application considered here is subsea robotic bathymetric mapping. In this context, SLAM allows a GPS-denied robot operating near the sea floor to create a self-consistent bathymetric map. This is accomplished using a Rao-Blackwellized Particle Filter (RBPF) whereby each particle maintains a hypothesis of the current vehicle state and map that is efficiently maintained using Distributed Particle Mapping. Through particle weighting and resampling, successive observations of the seafloor structure are used to improve the estimated trajectory and resulting map by enforcing map self consistency. The main contributions of this thesis are two novel map representations, either of which can be paired with the RBPF to perform SLAM. The first is a grid-based 2D depth map that is efficiently stored by exploiting redundancies between different maps. The second is a trajectory map representation that, instead of directly storing estimates of seabed depth, records the trajectory of each particle and synchronises it to a common log of bathymetric observations. Upon detecting a loop closure each particle is weighted by matching new observations to the current predictions. For the grid map approach this is done by extracting the predictions stored in the observed cells. For the trajectory map approach predictions are instead generated from a local reconstruction of their map using Gaussian Process Regression. While the former allows for faster map access the latter requires less memory and fully exploits the spatial correlation in the environment, allowing predictions of seabed depth to be generated in areas that were not directly observed previously. In this case particle resampling therefore not only enforces self-consistency in overlapping sections of the map but additionally enforces self-consistency between neighboring map borders. Both approaches are validated using multibeam sonar data collected from several missions of varying scale by a variety of different Unmanned Underwater Vehicles. These trials demonstrate how the corrections provided by both approaches improve the trajectory and map when compared to dead reckoning fused with Ultra Short Baseline or Long Baseline observations. Furthermore, results are compared with a pre-existing state of the art bathymetric SLAM technique, confirming that similar results can be achieved at a fraction of the computation cost. Lastly the added capabilities of the trajectory map are validated using two different bathymetric datasets. These demonstrate how navigation and mapping corrections can still be achieved when only sparse bathymetry is available (e.g. from a four beam Doppler Velocity Log sensor) or in missions where map overlap is minimal or even non-existent.
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Agarwal, Saurav. "Monocular vision based indoor simultaneous localisation and mapping for quadrotor platform." Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/7210.

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An autonomous robot acting in an unknown dynamic environment requires a detailed understanding of its surroundings. This information is provided by mapping algorithms which are necessary to build a sensory representation of the environment and the vehicle states. This aids the robot to avoid collisions with complex obstacles and to localize in six degrees of freedom i.e. x, y, z, roll, pitch and yaw angle. This process, wherein, a robot builds a sensory representation of the environment while estimating its own position and orientation in relation to those sensory landmarks, is known as Simultaneous Localisation and Mapping (SLAM). A common method for gauging environments are laser scanners, which enable mobile robots to scan objects in a non-contact way. The use of laser scanners for SLAM has been studied and successfully implemented. In this project, sensor fusion combining laser scanning and real time image processing is investigated. Hence, this project deals with the implementation of a Visual SLAM algorithm followed by design and development of a quadrotor platform which is equipped with a camera, low range laser scanner and an on-board PC for autonomous navigation and mapping of unstructured indoor environments. This report presents a thorough account of the work done within the scope of this project. It presents a brief summary of related work done in the domain of vision based navigation and mapping before presenting a real time monocular vision based SLAM algorithm. A C++ implementation of the visual slam algorithm based on the Extended Kalman Filter is described. This is followed by the design and development of the quadrotor platform. First, the baseline speci cations are described followed by component selection, dynamics modelling, simulation and control. The autonomous navigation algorithm is presented along with the simulation results which show its suitability to real time application in dynamic environments. Finally, the complete system architecture along with ight test results are described.
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Ihemadu, Okechukwu Clifford. "Robotic navigation in large environments using simultaneous localisation and mapping (SLAM)." Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602546.

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This thesis provides techniques to address some outstanding problems in robotic navigation in relatively large environments using simultaneous localisation and mapping (SLAM), resulting in improved competence and reliability of autonomous agents. Autonomous mobile agents are helpful in a diverse range of applications deemed as dull, dirty or dangerous for human operators including mining, defence and underwater explorations. In order to be fully autonomous the robot is required to incrementally construct a map of its vicinity and simultaneously localise itself within the environment based only on its on-board sensory data. However, the robot is confronted with a number of serious challenges that impair large-scale navigation and could even render SLAM results intractable in real time. This work provides efficient strategies for addressing such problems. The techniques presented include an effective method of reducing computational burden of updating the covariance matrix at every step, and cutting down the storage requirements. In addition, the usually complex and tedious task of transforming and fusing sub-maps into a single global map is simplified. Furthermore, an intelligent SLAM (I -SLAM) is introduced that enables accurate place recognition and minimise pose estimation errors. It also provides the means of adaptively adjusting to the nature of natural surface terrains for both indoor and outdoor environments. These techniques promise an enormous potential for autonomous agents operating in unknown environments in terms of consistency, accuracy and efficiency. Simulation results demonstrate the reliability and effectiveness of the system as a means of addressing some of the outstanding challenges with regards to large-scale SLAM performance
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Books on the topic "Simultaneous localisation and mapping"

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Milford, Michael John. Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Berlin: Springer, 2008.

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Będkowski, Janusz. Large-Scale Simultaneous Localization and Mapping. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1972-5.

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Harold, Weinberg, and Bencivenga Roberto Ph D, eds. Introduction to brain topography. New York: Plenum Press, 1991.

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Fernández-Madrigal, Juan-Antonio. Simultaneous localization and mapping for mobile robots: Introduction and methods. Hershey, PA: Information Science Reference, 2013.

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Flavin, Nora. Cloning and characterisation of the bovine activin receptor type II gene (ActRII): Its localisation to chromosome 2 (BTA2) by somatic cell genetic analysis and the genotyping of an associated microsatelltie UCD2. Dublin: University College Dublin, 1996.

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Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer, 2010.

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Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer London, Limited, 2007.

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Adaptive Sampling With Mobile Wsn Simultaneous Robot Localisation And Mapping Of Paramagnetic Spatiotemporal Fields. Institution of Engineering & Technology (IET), 2011.

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Lewis, Frank L., Koushil Sreenath, Muhammad F. Mysorewala, and Dan O. Popa. Adaptive Sampling with Mobile WSN: Simultaneous Robot Localisation and Mapping of Paramagnetic Spatio-Temporal Fields. Institution of Engineering & Technology, 2011.

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Janusz Będkowski. Large-Scale Simultaneous Localization and Mapping. Springer, 2022.

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Book chapters on the topic "Simultaneous localisation and mapping"

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Williams, Stefan B., Oscar Pizarro, Ian Mahon, and Matthew Johnson-Roberson. "Simultaneous Localisation and Mapping and Dense Stereoscopic Seafloor Reconstruction Using an AUV." In Experimental Robotics, 407–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00196-3_47.

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Jefferies, Margaret E., Wenrong Weng, Jesse T. Baker, and Michael Mayo. "Using Context to Solve the Correspondence Problem in Simultaneous Localisation and Mapping." In PRICAI 2004: Trends in Artificial Intelligence, 664–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28633-2_70.

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Thrun, Sebastian, and John J. Leonard. "Simultaneous Localization and Mapping." In Springer Handbook of Robotics, 871–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-30301-5_38.

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Ribas, David, Pere Ridao, and José Neira. "Simultaneous Localization and Mapping." In Springer Tracts in Advanced Robotics, 77–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14040-2_6.

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Song, Changhui. "Simultaneous Localization and Mapping." In Encyclopedia of Ocean Engineering, 1–8. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-10-6963-5_298-1.

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Stachniss, Cyrill. "Simultaneous Localization and Mapping." In Handbuch der Geodäsie, 1–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46900-2_49-1.

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Stachniss, Cyrill. "Simultaneous Localization and Mapping." In Handbuch der Geodäsie, 1–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-46900-2_49-2.

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Nissler, Christian, Maximilian Durner, Zoltán-Csaba Márton, and Rudolph Triebel. "Simultaneous Calibration and Mapping." In Springer Proceedings in Advanced Robotics, 791–800. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33950-0_68.

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Będkowski, Janusz. "Simultaneous Localization and Mapping." In Cognitive Intelligence and Robotics, 41–94. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1972-5_4.

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Song, Changhui. "Simultaneous Localization and Mapping." In Encyclopedia of Ocean Engineering, 1706–13. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-10-6946-8_298.

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Conference papers on the topic "Simultaneous localisation and mapping"

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Gayathri, T. R., R. P. Aneesh, and Gayathri R. Nayar. "Feature based simultaneous localisation and mapping." In 2017 IEEE International Conference on Circuits and Systems (ICCS). IEEE, 2017. http://dx.doi.org/10.1109/iccs1.2017.8326034.

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Diosdado, Jose Vazquez, and Ioseba Tena Ruiz. "Decentralised Simultaneous Localisation and Mapping for AUVs." In OCEANS 2007 - Europe. IEEE, 2007. http://dx.doi.org/10.1109/oceanse.2007.4302397.

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Zhao, Liang, Zhehua Mao, and Shoudong Huang. "Feature-Based SLAM: Why Simultaneous Localisation and Mapping?" In Robotics: Science and Systems 2021. Robotics: Science and Systems Foundation, 2021. http://dx.doi.org/10.15607/rss.2021.xvii.009.

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Scherer, Sebastian A., Daniel Dube, and Andreas Zell. "Using depth in visual simultaneous localisation and mapping." In 2012 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2012. http://dx.doi.org/10.1109/icra.2012.6224864.

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Rossides, Charalambos, and Stasinos Konstantopoulos. "Simultaneous Localisation and Mapping to Reach Linguistically-Defined Targets." In SETN '16: 9th Hellenic Conference on Artificial Intelligence. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2903220.2903232.

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Mahony, Robert, and Tarek Hamel. "A geometric nonlinear observer for simultaneous localisation and mapping." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8264002.

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Herath, D., Sarath Kodagoda, and Gamini Dissanayake. "Simultaneous Localisation and Mapping: A Stereo Vision Based Approach." In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2006. http://dx.doi.org/10.1109/iros.2006.281749.

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Williams, S., and I. Mahon. "Simultaneous localisation and mapping on the Great Barrier Reef." In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004. IEEE, 2004. http://dx.doi.org/10.1109/robot.2004.1308080.

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Moratuwage, Diluka, Martin Adams, and Felipe Inostroza. "$\delta$-Generalised Labelled Multi-Bernoulli Simultaneous Localisation and Mapping." In 2018 International Conference on Control, Automation and Information Sciences (ICCAIS). IEEE, 2018. http://dx.doi.org/10.1109/iccais.2018.8570448.

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Salas-Moreno, Renato F., Richard A. Newcombe, Hauke Strasdat, Paul H. J. Kelly, and Andrew J. Davison. "SLAM++: Simultaneous Localisation and Mapping at the Level of Objects." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.178.

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Reports on the topic "Simultaneous localisation and mapping"

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Kelley, Troy D. Using a Cognitive Architecture to Solve Simultaneous Localization and Mapping (SLAM) Problems. Fort Belvoir, VA: Defense Technical Information Center, April 2006. http://dx.doi.org/10.21236/ad1016045.

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Kelley, Troy D. Using a Cognitive Architecture to Solve Simultaneous Localization and Mapping (SLAM) Problems. Fort Belvoir, VA: Defense Technical Information Center, April 2006. http://dx.doi.org/10.21236/ada636872.

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Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41440.

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A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and 0.34/–0.05 m, respectively. Bathymetric data from another flight at Virginia Beach, VA, USA, demonstrates successful comparison (RMSE/bias of 0.17/0.06 m) in a secondary environment. UAS-derived engineering data products, total volume profiles and shoreline position, were congruent with those calculated from traditional topo-bathymetric surveys at Duck. Capturing both topography and bathymetry within a single flight, the presented multicamera system is more efficient than data acquisition with a single camera UAS; this advantage grows for longer stretches of coastline (10 km). Efficiency increases further with an on-board Global Navigation Satellite System–Inertial Navigation System (GNSS-INS) to eliminate ground control point (GCP) placement. The Appendix reprocesses the Virginia Beach flight with the GNSS–INS input and no GCPs.
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Christie, Benjamin, Osama Ennasr, and Garry Glaspell. Autonomous navigation and mapping in a simulated environment. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42006.

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Unknown Environment Exploration (UEE) with an Unmanned Ground Vehicle (UGV) is extremely challenging. This report investigates a frontier exploration approach, in simulation, that leverages Simultaneous Localization And Mapping (SLAM) to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, three-dimensional (3-D) LIDAR, and Red, Green, Blue and Depth (RGBD) cameras. The main goal of this effort is to leverage frontier-based exploration with a UGV to produce a 3-D map (up to 10 cm resolution). The solution provided leverages the Robot Operating System (ROS).
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Solares, Santiago D. Trimodal Tapping Mode Atomic Force Microscopy. Simultaneous 4D Mapping of Conservative and Dissipative Probe-Sample Interactions of Energy-Relevant Materials. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1215400.

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Solares, Santiago D. Final Technical Report for Award DESC0011912, "Trimodal Tapping Mode Atomic Force Microscopy: Simultaneous 4D Mapping of Conservative and Dissipative Probe-Sample Interactions of Energy-Relevant Materials”. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1393854.

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.
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Christie, Benjamin, Osama Ennasr, and Garry Glaspell. ROS integrated object detection for SLAM in unknown, low-visibility environments. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42385.

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Integrating thermal (or infrared) imagery on a robotics platform allows Unmanned Ground Vehicles (UGV) to function in low-visibility environments, such as pure darkness or low-density smoke. To maximize the effectiveness of this approach we discuss the modifications required to integrate our low-visibility object detection model on a Robot Operating System (ROS). Furthermore, we introduce a method for reporting detected objects while performing Simultaneous Localization and Mapping (SLAM) by generating bounding boxes and their respective transforms in visually challenging environments.
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Paterson, Andrew H., Yehoshua Saranga, and Dan Yakir. Improving Productivity of Cotton (Gossypsum spp.) in Arid Region Agriculture: An Integrated Physiological/Genetic Approach. United States Department of Agriculture, December 1999. http://dx.doi.org/10.32747/1999.7573066.bard.

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Objectives: We seek to establish the basis for improving cotton productivity under arid conditions, by studying the water use efficiency - evaporative cooling interrelationship. Specifically, we will test the hypothesis that cotton productivity under arid conditions can be improved by combining high seasonal WUE with efficient evaporative cooling, evaluate whether high WUE and/or evaporative cooling are based on specific physiological factors such as diurnal flexibility in stomatal conductance, stomatal density, photosynthetic capacity, chlorophyll fluorescence, and plant water status. Genes influencing both WUE and evaporative cooling, as well as other parameters such as economic products (lint yield, quality, harvest index) of cotton will also be mapped, in order to evaluate influences of water relations on these parameters. Approach: Carbon isotope ratio will be used to evaluate WUE, accompanied by additional parameters to elucidate the relationship between WUE, evaporative cooling, and cotton productivity. A detailed RFLP map will be used to determine the number, location, and phenotypic effects of genes underlying genetic variation in WUE between cultivated cottons, as well as test associations of these genes with traits of economic importance such as harvest index, lint yield, and lint quality. Major Conclusions: Productivity and quality of cotton grown under well-watered versus water-limited conditions was shown to be partly accounted for by different quantitative trait loci (QTLs). Among a suite of physiological traits often found to differ between genotypes adapted to arid versus well-watered conditions, genetic mapping implicated only reduced plant osmotic potential in improved cotton productivity under arid conditions. Our findings clearly implicate OP as a major component of cotton adaptation to arid conditions. However, testing of further physiological hypotheses is clearly needed to account for additional QTL alleles conferring higher seed-cotton yield under arid conditions, such as three of the five we found. Near-isogenic lines being made for QTLs discovered herein will offer a powerful new tool useful toward identification of the underlying gene(s) by using fine-scale mapping approaches (Paterson et al 1990). Implications: Adaptation to both arid and favorable conditions can be combined into the same genotype. We have identified diagnostic DNA markers that are being applied to creation of such desirable genotypes. Simultaneous improvement of productivity (and/or quality) for both arid and irrigated conditions will require more extensive field testing and the manipulation of larger numbers of genes, reducing the expected rate of genetic gain These difficulties may be at least partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers. Genomic tools and approaches may expedite adaptation of crops to arid cultivation, help to test roles of additional physiological factors, and guide the isolation of the underlying genes that protect crop performance under arid conditions.
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Fahima, Tzion, and Jorge Dubcovsky. Map-based cloning of the novel stripe rust resistance gene YrG303 and its use to engineer 1B chromosome with multiple beneficial traits. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598147.bard.

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Research problem: Bread wheat (Triticumaestivum) provides approximately 20% of the calories and proteins consumed by humankind. As the world population continues to increase, it is necessary to improve wheat yields, increase grain quality, and minimize the losses produced by biotic and abiotic stresses. Stripe rust, caused by Pucciniastriiformisf. sp. tritici(Pst), is one of the most destructive diseases of wheat. The new pathogen races are more virulent and aggressive than previous ones and have produced large economic losses. A rich source for stripe-rust resistance genes (Yr) was found in wild emmer wheat populations from Israel. Original Project goals: Our long term goal is to identify, map, clone, characterize and deploy in breeding, novel wild emmer Yr genes, and combine them with multiple beneficial traits. The current study was aiming to map and clone YrG303 and Yr15, located on chromosome 1BS and combine them with drought resistance and grain quality genes. Positional cloning of YrG303/Yr15: Fine mapping of these genes revealed that YrG303 is actually allelic to Yr15. Fine genetic mapping using large segregating populations resulted in reduction of the genetic interval spanning Yr15 to less than 0.1 cM. Physical mapping of the YrG303/Yr15 locus was based on the complete chromosome 1BS physical map of wheat constructed by our group. Screening of 1BS BAC library with Yr15 markers revealed a long BAC scaffold covering the target region. The screening of T. dicoccoidesaccession-specific BAC library with Yr15 markers resulted in direct landing on the target site. Sequencing of T. dicoccoidesBAC clones that cover the YrG303/Yr15 locus revealed a single candidate gene (CG) with conserved domains that may indicate a role in disease resistance response. Validation of the CG was carried out using EMS mutagenesis (loss-of- function approach). Sequencing of the CG in susceptible yr15/yrG303 plants revealed three independent mutants that harbour non-functional yr15/yrG303 alleles within the CG conserved domains, and therefore validated its function as a Pstresistance gene. Evaluation of marker-assisted-selection (MAS) for Yr15. Introgressions of Yr15 into cultivated wheat are widely used now. Recently, we have shown that DNA markers linked to Yr15 can be used as efficient tools for introgression of Yr15 into cultivated wheat via MAS. The developed markers were consistent and polymorphic in all 34 tested introgressions and are the most recommended markers for the introgression of Yr15. These markers will facilitate simultaneous selection for multiple Yr genes and help to avoid escapees during the selection process. Engineering of improved chromosome 1BS that harbors multiple beneficial traits. We have implemented the knowledge and genetic resources accumulated in this project for the engineering of 1B "super-chromosome" that harbors multiple beneficial traits. We completed the generation of a chromosome including the rye 1RS distal segment associated with improved drought tolerance with the Yr gene, Yr15, and the strong gluten allele 7Bx-over-expressor (7Bxᴼᴱ). We have completed the introgression of this improved chromosome into our recently released variety Patwin-515HP and our rain fed variety Kern, as well as to our top breeding lines UC1767 and UC1745. Elucidating the mechanism of resistance exhibited by Yr36 (WKS1). The WHEAT KINASE START1 (WKS1) resistance gene (Yr36) confers partial resistance to Pst. We have shown that wheat plants transformed with WKS1 transcript are resistant to Pst. WKS1 is targeted to the chloroplast where it phosphorylates the thylakoid-associatedascorbateperoxidase (tAPX) and reduces its ability to detoxify peroxides. Based on these results, we propose that the phosphorylation of tAPX by WKS1 reduces the ability of the cells to detoxify ROS and contributes to cell death. Distribution and diversity of WKS in wild emmer populations. We have shown that WKS1 is present only in the southern distribution range of wild emmer in the Fertile Crescent. Sequence analysis revealed a high level of WKS1 conservation among wild emmer populations, in contrast to the high level of diversity observed in NB-LRR genes. This phenomenon shed some light on the evolution of genes that confer partial resistance to Pst. Three new WKS1 haplotypes displayed a resistance response, suggesting that they can be useful to improve wheat resistance to Pst. In summary, we have improved our understanding of cereals’ resistance mechanisms to rusts and we have used that knowledge to develop improved wheat varieties.
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