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bibliografia.bib
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# En este archivo se coloca la bibliografía en formato BibTeX, se recomienda buscar el documento en scholar.google.com y luego hacer click en "citar" y seleccionar el formato "BibTeX" para obtener el snippet que debe ir aquí.
% Recuerde que hay que citar estas entradas en el documento para que aparezcan en la bibliografía. e.g. \cite{schwab2002cure}
% Recuerde NO reemplazar los "and" por "y" en los campos de author, ¡Puesto que "and" es una palabra clave para separarlos!
@book{anis_koubaa_robot_2016,
address = {London},
edition = {1},
series = {Studies in {Computational} {Intelligence}},
title = {Robot {Operating} {System} ({ROS})},
volume = {1},
isbn = {978-3-319-26052-5},
url = {https://link.springer.com/book/10.1007/978-3-319-26054-9},
language = {en},
urldate = {2022-06-09},
publisher = {Springer International Publishing},
author = {Anis Koubaa},
month = jan,
year = {2016},
file = {Robot Operating System (ROS).pdf:C\:\\Users\\cleme\\Zotero\\storage\\7K44KMZA\\Robot Operating System (ROS).pdf:application/pdf;Snapshot:C\:\\Users\\cleme\\Zotero\\storage\\3BIVYU2F\\978-3-319-26054-9.html:text/html},
}
@book{fahimi_autonomous_2009,
address = {Boston, MA},
title = {Autonomous {Robots}},
isbn = {978-0-387-09537-0 978-0-387-09538-7},
url = {http://link.springer.com/10.1007/978-0-387-09538-7},
language = {en},
urldate = {2022-06-16},
publisher = {Springer US},
author = {Fahimi, Farbod},
year = {2009},
doi = {10.1007/978-0-387-09538-7},
file = {Fahimi - 2009 - Autonomous Robots.pdf:C\:\\Users\\cleme\\Zotero\\storage\\9Z689HEQ\\Fahimi - 2009 - Autonomous Robots.pdf:application/pdf},
}
@inproceedings{hirose_three_1991,
title = {Three basic types of locomotion in mobile robots},
doi = {10.1109/ICAR.1991.240483},
abstract = {The types of locomotion in mobile robots, the fundamental problem in the design of mobile robot, are discussed and it is pointed out that there are three fundamental configurations in the mobile robot: wheels and crawler track; legs; and an articulated body. The characteristics of these configurations are discussed. Some of the examples of mobile robot are given.{\textless}{\textgreater}},
booktitle = {Fifth {International} {Conference} on {Advanced} {Robotics} '{Robots} in {Unstructured} {Environments}},
author = {Hirose, S.},
month = jun,
year = {1991},
keywords = {Actuators, Animals, Crawlers, Leg, Legged locomotion, Mechanical engineering, Mobile robots, Production facilities, Service robots, Wheels},
pages = {12--17 vol.1},
file = {IEEE Xplore Abstract Record:C\:\\Users\\cleme\\Zotero\\storage\\8VTBPJ2A\\240483.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\ZZZHWKRX\\Hirose - 1991 - Three basic types of locomotion in mobile robots.pdf:application/pdf},
}
@inproceedings{takaya_simulation_2016,
title = {Simulation environment for mobile robots testing using {ROS} and {Gazebo}},
doi = {10.1109/ICSTCC.2016.7790647},
abstract = {In the process of development a control strategy for mobile robots, simulation is important for testing the software components, robot behavior and control algorithms in different surrounding environments. In this paper we introduce a simulation environment for mobile robots based on ROS and Gazebo. We show that after properly creating the robot models under Gazebo, the code developed for the simulation process can be directly implemented in the real robot without modifications. In this paper autonomous navigation tasks and 3D-mapping simulation using control programs under ROS are presented. Both the simulation and experimental results agree very well and show the usability of the developed environment.},
booktitle = {2016 20th {International} {Conference} on {System} {Theory}, {Control} and {Computing} ({ICSTCC})},
author = {Takaya, Kenta and Asai, Toshinori and Kroumov, Valeri and Smarandache, Florentin},
month = oct,
year = {2016},
keywords = {Software, ROS, Gazebo, 3D mapping, Computational modeling, Mobile robot simulation, Mobile robots, Object oriented modeling, Robot kinematics, Robot sensing systems},
pages = {96--101},
file = {IEEE Xplore Abstract Record:C\:\\Users\\cleme\\Zotero\\storage\\HS7Y2AXZ\\7790647.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\EWRY3LDE\\Takaya et al. - 2016 - Simulation environment for mobile robots testing u.pdf:application/pdf},
}
@article{lizama_redes_nodate,
title = {Redes de computadores {Arquitectura} {Cliente} - {Servidor}},
language = {es},
author = {Lizama, Oscar and Kindley, Geordy and Morales, Javier Ignacio Jeria and Gonzales, Agustın},
pages = {8},
file = {Lizama et al. - Redes de computadores Arquitectura Cliente - Servi.pdf:C\:\\Users\\cleme\\Zotero\\storage\\MQQWTIQJ\\Lizama et al. - Redes de computadores Arquitectura Cliente - Servi.pdf:application/pdf},
}
@article{kam_rviz_2015,
title = {{RViz}: a toolkit for real domain data visualization},
volume = {60},
issn = {1018-4864, 1572-9451},
shorttitle = {{RViz}},
url = {http://link.springer.com/10.1007/s11235-015-0034-5},
doi = {10.1007/s11235-015-0034-5},
abstract = {In computational science and computer graphics, there is a strong requirement to represent and visualize information in the real domain, and many visualization data structures and algorithms have been proposed to achieve this aim. Unfortunately, the dataflow model that is often selected to address this issue in visualization systems is not flexible enough to visualize newly invented data structures and algorithms because this scheme can accept only specific data structures. To address this problem, we propose a new visualization tool, RViz, which is independent of the input information data structures. Since there is no requirement for additional efforts to manage the flow networks and the interface to abstracted information is simple in RViz, any scientific information visualization algorithms are easier to implement than the dataflow model. In this paper, we provide case studies in which we have successfully implemented new data structures and related algorithms using RViz, including geometry synthesis, distance field representation, and implicit surface reconstruction. Through these cases, we show how RViz helps users visualize and understand any hidden insights in input information.},
language = {en},
number = {2},
urldate = {2022-06-18},
journal = {Telecommunication Systems},
author = {Kam, Hyeong Ryeol and Lee, Sung-Ho and Park, Taejung and Kim, Chang-Hun},
month = oct,
year = {2015},
pages = {337--345},
file = {Kam et al. - 2015 - RViz a toolkit for real domain data visualization.pdf:C\:\\Users\\cleme\\Zotero\\storage\\J8EA3BNY\\Kam et al. - 2015 - RViz a toolkit for real domain data visualization.pdf:application/pdf},
}
@incollection{huang_robot_2016,
title = {Robot {Localization}: {An} {Introduction}},
isbn = {978-0-471-34608-1},
shorttitle = {Robot {Localization}},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/047134608X.W8318},
abstract = {Robot localization is the process of determining where a mobile robot is located with respect to its environment. Localization is one of the most fundamental competencies required by an autonomous robot as the knowledge of the robot's own location is an essential precursor to making decisions about future actions. In a typical robot localization scenario, a map of the environment is available and the robot is equipped with sensors that observe the environment as well as monitor its own motion. The localization problem then becomes one of estimating the robot position and orientation within the map using information gathered from these sensors. Robot localization techniques need to be able to deal with noisy observations and generate not only an estimate of the robot location but also a measure of the uncertainty of the location estimate. This article provides an introduction to estimation of theoretic solutions to the robot localization problem. It begins by discussing the mathematical models used to describe the robot motion and observations from the sensors. Two of the most common probabilistic techniques, the extended Kalman filter and the particle filter, that can be used to combine information from sensors to compute an estimate of the robot location are then discussed in detail and illustrated by simple examples. A brief summary of the large body of literature on robot localization is presented next. Appendices that present the essential mathematical background and alternative techniques are provided. The MATLAB code of the localization algorithms is also available.},
language = {en},
urldate = {2022-06-18},
booktitle = {Wiley {Encyclopedia} of {Electrical} and {Electronics} {Engineering}},
publisher = {John Wiley \& Sons, Ltd},
author = {Huang, Shoudong and Dissanayake, Gamini},
year = {2016},
doi = {10.1002/047134608X.W8318},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/047134608X.W8318},
keywords = {Kalman filter, least squares, localization, Markov localization, mobile robots, particle filter},
pages = {1--10},
file = {Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\NTTNXRF2\\Huang y Dissanayake - 2016 - Robot Localization An Introduction.pdf:application/pdf},
}
@article{reyes_mobile_2015,
title = {Mobile {Robot} {Navigation} {Assisted} by {GPS}},
volume = {13},
issn = {1548-0992},
doi = {10.1109/TLA.2015.7164217},
abstract = {Paper presents simulation and operation of a mobile robot using GPS in navigation. It is used SLAM algorithm to obtain a map, a path planner algorithm called Wavefront, and a VHF navigation obstacle evasion algorithm. A Player/Stage is utilized in simulation and the real navigation of a mobile robot is tested.},
number = {6},
journal = {IEEE Latin America Transactions},
author = {Reyes, Daniel and Millan, Ginno and Osorio-Corparan, Roman and Lefranc, Gaston},
month = jun,
year = {2015},
note = {Conference Name: IEEE Latin America Transactions},
keywords = {Global Position System (GPS), Global Positioning System, mobile robots, Mobile robots, Silicon, Simultaneous localization and mapping, Simultaneous Localization and Mapping (SLAM), Vector Field Histogram (VFH)},
pages = {1915--1920},
file = {IEEE Xplore Abstract Record:C\:\\Users\\cleme\\Zotero\\storage\\ZYYIB7KD\\7164217.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\GPMH2L3P\\Reyes et al. - 2015 - Mobile Robot Navigation Assisted by GPS.pdf:application/pdf},
}
@inproceedings{megalingam_ros_2019,
title = {{ROS} {Based} {Control} of {Robot} {Using} {Voice} {Recognition}},
doi = {10.1109/ICISC44355.2019.9036443},
abstract = {Voice-based smart home applications have taken a rapid growth in the past few years. Voice recognition is the ability of the system to receive, interpret, analyze and carry out the spoken commands. This paper proposes a ROS based voice - controlled robot, which runs using a differential drive mechanism and takes the voice commands from the user and moves a wheeled robot accordingly. The system is based on a statistical model such as the Hidden Markov Model (HMM). The HMM approach to speech enhancement relies on the Viterbi Algorithm.},
booktitle = {2019 {Third} {International} {Conference} on {Inventive} {Systems} and {Control} ({ICISC})},
author = {Megalingam, Rajesh Kannan and Reddy, Racharla Shriya and Jahnavi, Yannam and Motheram, Manaswini},
month = jan,
year = {2019},
keywords = {Software, ROS, Mobile robots, Robot kinematics, DC motors, Hidden Markov models, Pocket Sphinx, Speech recognition, voice recognition, voice-controlled robot},
pages = {501--507},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\BQYTVASG\\Megalingam et al. - 2019 - ROS Based Control of Robot Using Voice Recognition.pdf:application/pdf},
}
@book{thrun_probabilistic_2005,
address = {Cambridge, Mass},
series = {Intelligent robotics and autonomous agents},
title = {Probabilistic robotics},
isbn = {978-0-262-20162-9},
language = {en},
publisher = {MIT Press},
author = {Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter},
year = {2005},
note = {OCLC: ocm58451645},
keywords = {Probabilities, Robotics},
file = {Thrun et al. - 2005 - Probabilistic robotics.pdf:C\:\\Users\\cleme\\Zotero\\storage\\DK7WZWX4\\Thrun et al. - 2005 - Probabilistic robotics.pdf:application/pdf},
}
@article{wang_grid-based_2018,
title = {A {Grid}-{Based} {Localization} {Algorithm} for {Wireless} {Sensor} {Networks} {Using} {Connectivity} and {RSS} {Rank}},
volume = {6},
issn = {2169-3536},
doi = {10.1109/ACCESS.2018.2804381},
abstract = {To improve localization accuracy and reduce system costs, a new range-free localization algorithm for wireless sensor networks using connectivity and received signal strength (RSS) rank is proposed. An unknown node is first localized in an initial residence area according to the connectivity constraints. Then, the residence area is refined using the RSS rank vector. The RSS rank vector of an unknown node is formed from the ranks of the RSS values obtained from neighboring anchors. The estimated location of the unknown node is the centroid of the refined residence area. The proposed localization algorithm uses a grid scan approach to avoid the complex geometric computations. This algorithm is improved by using an adaptive strategy to determine the grid size. The performance of these methods is examined via analysis and simulation. The results obtained verify that the proposed approaches provide better localization accuracy than competing algorithms in the literature.},
journal = {IEEE Access},
author = {Wang, Zengfeng and Zhang, Hao and Lu, Tingting and Gulliver, T. Aaron},
year = {2018},
note = {Conference Name: IEEE Access},
keywords = {Algorithm design and analysis, Approximation algorithms, connectivity, Estimation, Fading channels, Lenses, localization, received signal strength, Sensors, Wireless sensor networks},
pages = {8426--8439},
}
@inproceedings{xiaoyu_adaptive_2018,
title = {On {Adaptive} {Monte} {Carlo} {Localization} {Algorithm} for the {Mobile} {Robot} {Based} on {ROS}},
doi = {10.23919/ChiCC.2018.8482698},
abstract = {This paper proposes an adaptive Monte Carlo location (MCL) algorithm in stages to improve the common problems existed in the traditional MCL method, such as the high computational complexity, and the hijacked circumstance for the mobile robot. Firstly, the current positioned state, namely global localization or local localization, is judged. Secondly, different particles are assigned to conduct localization and tracking based on the different status of positioning allocation. In addition, the accuracy of the positioning system is used to detect whether the robot has been hijacked or not. The research of SLAM carried out on the Robot Operating System (ROS) shows that the proposed method is effective in achieving an accurate localization and reducing the computational complexity. It is suitable for indoor mobile robot SLAM.},
booktitle = {2018 37th {Chinese} {Control} {Conference} ({CCC})},
author = {Xiaoyu, Wang and Caihong, Li and Li, Song and Ning, Zhang and Hao, Fu},
month = jul,
year = {2018},
note = {ISSN: 1934-1768},
keywords = {SLAM, indoor positioning, Monte Carlo location algorithm (MCL), ROS robot},
pages = {5207--5212},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\V8KSWJUT\\Xiaoyu et al. - 2018 - On Adaptive Monte Carlo Localization Algorithm for.pdf:application/pdf},
}
@inproceedings{dos_reis_quantitative_2019,
title = {A {Quantitative} {Study} of {Tuning} {ROS} {Adaptive} {Monte} {Carlo} {Localization} {Parameters} and their {Effect} on an {AGV} {Localization}},
doi = {10.1109/ICAR46387.2019.8981601},
abstract = {One key aspect of the use of Automated Guided Vehicles in an industrial environment is its localization effectiveness. Among the existing techniques, the use of a laser scanner stands out. Besides, the Adaptive Monte Carlo Localization algorithm has become a reference in academic research. Despite many works use the AMCL package, they do not fully discuss the effect of the parameters change on the algorithm response and its tuning. This work aims to examine the distinct influence of each tested parameter in AGV localization. We performed the experiments in the same environment, and the AGV ran the same path to enable comparison against the parameters variation. For the 7 parameters tested, the results show the relationship between the package parameters and the localization response behavior. Although the article does not aim to propose the best parameter tuning, the results show the direction to follow in values adjusting.},
booktitle = {2019 19th {International} {Conference} on {Advanced} {Robotics} ({ICAR})},
author = {dos Reis, Wallace Pereira Neves and Morandin, Orides and Vivaldini, Kelen Cristiane Teixeira},
month = dec,
year = {2019},
pages = {302--307},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\2GF5XW9V\\dos Reis et al. - 2019 - A Quantitative Study of Tuning ROS Adaptive Monte .pdf:application/pdf},
}
@inproceedings{sankalprajan_comparative_2020,
title = {Comparative analysis of {ROS} based {2D} and {3D} {SLAM} algorithms for {Autonomous} {Ground} {Vehicles}},
doi = {10.1109/INCET49848.2020.9154101},
abstract = {Simultaneous localization and mapping algorithm (SLAM) is a technique for estimating sensor motion and reconstructing the structure in an unknown environment. SLAM is extensively used in the concept of autonomous driving or navigation which helps robotic vehicles to move autonomously. This paper presents a comparative analysis of different ROS based 2D SLAM algorithms such as GMapping, Hector SLAM, Karto SLAM and 3D SLAM algorithm such as Real-Time Appearance-Based Mapping. Scenarios with a scaling factor resembling an underground parking was built in real-time and simulation for analysis and validation purposes. The maps generated by applying the respective SLAM algorithms in real-time and simulation was analyzed and validated quantitatively based on quality and accuracy using the Structure Similarity Index.},
booktitle = {2020 {International} {Conference} for {Emerging} {Technology} ({INCET})},
author = {Sankalprajan, P and Sharma, Thrilochan and Perur, Hamsa Datta and Sekhar Pagala, Prithvi},
month = jun,
year = {2020},
keywords = {RTAB-Map, Simultaneous localization and mapping, Autonomous vehicles, GMapping, Hector SLAM, Karto SLAM, Measurement, Real-time systems, robotic vehicle, Service robots, Structure Similarity Index},
pages = {1--6},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\A54B6X75\\Sankalprajan et al. - 2020 - Comparative analysis of ROS based 2D and 3D SLAM a.pdf:application/pdf},
}
@article{gul_comprehensive_2019,
title = {A comprehensive study for robot navigation techniques},
volume = {6},
issn = {null},
url = {https://doi.org/10.1080/23311916.2019.1632046},
doi = {10.1080/23311916.2019.1632046},
abstract = {An intelligent autonomous robot is required in various applications such as space, transportation, industry, and defense. Mobile robots can also perform several tasks like material handling, disaster relief, patrolling, and rescue operation. Therefore, an autonomous robot is required that can travel freely in a static or a dynamic environment. Smooth and safe navigation of mobile robot through cluttered environment from start position to goal position with following safe path and producing optimal path length is the main aim of mobile robot navigation. Regarding this matter, several techniques have been explored by researchers for robot navigation path planning. An effort has been made in this article to study several navigation techniques, which are well suited for the static and dynamic environment and can be implemented for real-time navigation of mobile robot.},
number = {1},
urldate = {2022-06-19},
journal = {Cogent Engineering},
author = {Gul, Faiza and Rahiman, Wan and Nazli Alhady, Syed Sahal},
editor = {Chen, Kun},
month = jan,
year = {2019},
note = {Publisher: Cogent OA
\_eprint: https://doi.org/10.1080/23311916.2019.1632046},
keywords = {AGV, Artificial intelligence, fuzzy logic, neural network},
pages = {1632046},
file = {Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\Y62VE2VR\\Gul et al. - 2019 - A comprehensive study for robot navigation techniq.pdf:application/pdf;Snapshot:C\:\\Users\\cleme\\Zotero\\storage\\AXDUB853\\23311916.2019.html:text/html},
}
@misc{noauthor_global_nodate,
title = {Global and {Local} {Path} {Planning} {Study} in a {ROS}-{Based} {Research} {Platform} for {Autonomous} {Vehicles}},
url = {https://www.hindawi.com/journals/jat/2018/6392697/},
urldate = {2022-06-09},
author = {Pablo Marin-Plaza and Ahmed Hussein and David Martin and Arturo de la Escalera},
journal = {Journal of Advanced Transportation},
booktitle = {2018 Cooperative Systems for Autonomous Vehicles},
month = feb,
year = {2018},
volume = {2018},
file = {Global and Local Path Planning Study in a ROS-Base.pdf:C\:\\Users\\cleme\\Zotero\\storage\\BLVBRU9T\\Global and Local Path Planning Study in a ROS-Base.pdf:application/pdf},
}
@article{candra_application_2021,
title = {Application of {A}-{Star} {Algorithm} on {Pathfinding} {Game}},
volume = {1898},
issn = {1742-6588, 1742-6596},
url = {https://iopscience.iop.org/article/10.1088/1742-6596/1898/1/012047},
doi = {10.1088/1742-6596/1898/1/012047},
abstract = {Pathfinding is the method for determining the shortest path. Pathfinding is widely used in various fields of Computer Science. One of them is game development. This research will design and analyze the pathfinding using the A-Star algorithm and implement it on a tree planting game. The Artificial Intelligence in the game will find its own shortest path from the start node to the goal node. The heuristic of A-Star is the Manhattan Distance that allows movement in four different directions. The result shows that the number of visited nodes will increase if the grid has many obstacle nodes, and the average time of the A-Star pathfinding process is 0.0732 seconds.},
language = {en},
number = {1},
urldate = {2022-06-19},
journal = {Journal of Physics: Conference Series},
author = {Candra, Ade and Budiman, Mohammad Andri and Pohan, Rahmat Irfan},
month = jun,
year = {2021},
pages = {012047},
file = {Candra et al. - 2021 - Application of A-Star Algorithm on Pathfinding Gam.pdf:C\:\\Users\\cleme\\Zotero\\storage\\VMX2V2TI\\Candra et al. - 2021 - Application of A-Star Algorithm on Pathfinding Gam.pdf:application/pdf},
}
@article{grisetti_fast_2007,
series = {Simultaneous {Localisation} and {Map} {Building}},
title = {Fast and accurate {SLAM} with {Rao}–{Blackwellized} particle filters},
volume = {55},
issn = {0921-8890},
url = {https://www.sciencedirect.com/science/article/pii/S092188900600145X},
doi = {10.1016/j.robot.2006.06.007},
abstract = {Rao–Blackwellized particle filters have become a popular tool to solve the simultaneous localization and mapping problem. This technique applies a particle filter in which each particle carries an individual map of the environment. Accordingly, a key issue is to reduce the number of particles and/or to make use of compact map representations. This paper presents an approximative but highly efficient approach to mapping with Rao–Blackwellized particle filters. Moreover, it provides a compact map model. A key advantage is that the individual particles can share large parts of the model of the environment. Furthermore, they are able to reuse an already computed proposal distribution. Both techniques substantially speed up the overall filtering process and reduce the memory requirements. Experimental results obtained with mobile robots in large-scale indoor environments and based on published standard datasets illustrate the advantages of our methods over previous mapping approaches using Rao–Blackwellized particle filters.},
language = {en},
number = {1},
urldate = {2022-06-19},
journal = {Robotics and Autonomous Systems},
author = {Grisetti, Giorgio and Tipaldi, Gian Diego and Stachniss, Cyrill and Burgard, Wolfram and Nardi, Daniele},
month = jan,
year = {2007},
keywords = {Grid map, Informed proposal, Rao–Blackwellized particle filter, SLAM},
pages = {30--38},
file = {ScienceDirect Snapshot:C\:\\Users\\cleme\\Zotero\\storage\\IZHB3I2R\\S092188900600145X.html:text/html;Versión enviada:C\:\\Users\\cleme\\Zotero\\storage\\F3WPVADH\\Grisetti et al. - 2007 - Fast and accurate SLAM with Rao–Blackwellized part.pdf:application/pdf},
}
@inproceedings{liu_research_2021,
title = {Research on {SLAM} {Algorithm} and {Navigation} of {Mobile} {Robot} {Based} on {ROS}},
doi = {10.1109/ICMA52036.2021.9512584},
abstract = {As an important research direction of mobile robots, SLAM is the core technology to realize intelligent autonomous mobile robots. For positioning, the robot needs a consistent map, for obtaining a map, the robot makes a good estimate of its position. This interdependence between positioning and mapping makes the SLAM problem difficult and necessary. This article first summarizes the representation method of the environment map, uses the ROS mobile robot to map the indoor environment, compares the mapping effect of the Gmapping algorithm and the Cartographer algorithm, analyzes the results of the mapping, and proposes the optimal mapping plan. Aiming at the problem of simultaneous localization and mapping of robots, a ROS-based solution is proposed. Compare Dijkstra, A * algorithm and Dynamic Window Approach, and choose the best navigation algorithm.},
booktitle = {2021 {IEEE} {International} {Conference} on {Mechatronics} and {Automation} ({ICMA})},
author = {Liu, Bin and Guan, Zhiwei and Li, Bin and Wen, Guoqiang and Zhao, Yu},
month = aug,
year = {2021},
note = {ISSN: 2152-744X},
keywords = {ROS, Laser radar, Simultaneous localization and mapping, Navigation, Heuristic algorithms, Path planning, Cartographer algorithm, Gmapping algorithm, Mechatronics, Optimization methods, SLAM mapping},
pages = {119--124},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\FAN97RDI\\Liu et al. - 2021 - Research on SLAM Algorithm and Navigation of Mobil.pdf:application/pdf},
}
@inproceedings{chan_lidar-based_2021,
title = {{LiDAR}-{Based} {3D} {SLAM} for {Indoor} {Mapping}},
doi = {10.1109/ICCAR52225.2021.9463503},
abstract = {Aiming to develop methods for real-time 3D scanning of building interiors, this work evaluates the performance of state-of-the-art LiDAR-based approaches for 3D simultaneous localisation and mapping (SLAM) in indoor environments. A simulation framework using ROS and Gazebo has been implemented to compare different methods based on LiDAR odometry and mapping (LOAM). The featureless environments typically found in interiors of commercial and industrial buildings pose significant challenges for LiDAR-based SLAM frameworks, resulting in drift or breakdown of the processes. The results from this paper provide performance criteria for indoor SLAM applications, comparing different room topologies and levels of clutter. The modular nature of the simulation environment provides a framework for future SLAM development and benchmarking specific to indoor environments.},
booktitle = {2021 7th {International} {Conference} on {Control}, {Automation} and {Robotics} ({ICCAR})},
author = {Chan, Teng Hooi and Hesse, Henrik and Ho, Song Guang},
month = apr,
year = {2021},
note = {ISSN: 2251-2454},
keywords = {SLAM, Laser radar, Simultaneous localization and mapping, Three-dimensional displays, Real-time systems, Benchmark testing, Buildings, Indoor environment, Indoor Mapping, Lidar Odometry},
pages = {285--289},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\5XFBJMYN\\Chan et al. - 2021 - LiDAR-Based 3D SLAM for Indoor Mapping.pdf:application/pdf},
}
@article{graetz_online_nodate,
title = {Online {Appendix} for “{Robots} at {Work}”},
language = {en},
author = {Graetz, Georg and Michaels, Guy},
pages = {28},
file = {Graetz y Michaels - Online Appendix for “Robots at Work”.pdf:C\:\\Users\\cleme\\Zotero\\storage\\XF3RVJ2Z\\Graetz y Michaels - Online Appendix for “Robots at Work”.pdf:application/pdf},
}
@article{quigley_programming_nodate,
title = {Programming {Robots} with {ROS}},
language = {en},
author = {Quigley, Morgan and Gerkey, Brian and Smart, William D},
pages = {447},
file = {Quigley et al. - Programming Robots with ROS.pdf:C\:\\Users\\cleme\\Zotero\\storage\\URC3VWJ9\\Quigley et al. - Programming Robots with ROS.pdf:application/pdf},
}
@book{russell_artificial_2010,
address = {Upper Saddle River},
edition = {3rd ed},
series = {Prentice {Hall} series in artificial intelligence},
title = {Artificial intelligence: a modern approach},
isbn = {978-0-13-604259-4},
shorttitle = {Artificial intelligence},
language = {en},
publisher = {Prentice Hall},
author = {Russell, Stuart J. and Norvig, Peter and Davis, Ernest},
year = {2010},
keywords = {Artificial intelligence},
file = {Russell et al. - 2010 - Artificial intelligence a modern approach.pdf:C\:\\Users\\cleme\\Zotero\\storage\\5D66CDR5\\Russell et al. - 2010 - Artificial intelligence a modern approach.pdf:application/pdf},
}
@article{rivera_taiba_efectos_2019,
title = {Efectos de la automatización en el empleo en {Chile}},
volume = {34},
issn = {0718-8870},
url = {http://www.scielo.cl/scielo.php?script=sci_abstract&pid=S0718-88702019000100003&lng=es&nrm=iso&tlng=pt},
doi = {10.4067/S0718-88702019000100003},
abstract = {Resumen:El presente trabajo analiza los efectos de la automatización en el mercado laboral chileno. Se emplea un modelo de equilibrio general, en el que se considera separadamente la inversión en capital robótico y la inversión en capital tradicional, permitiendo el estudio de los efectos de complementariedad y sustitución que se verifican en relación con el factor trabajo. En particular, el modelo trata el capital robótico como un sustituto directo del trabajo, mientras que incorpora al capital tradicional como complementario a este. Al someter a la economía a shocks en los precios de capital robótico, se puede estudiar los efectos en el consumo, el empleo, los salarios y el PIB. Los resultados indican que una caída en el precio de compra internacional de capital robótico produce un impacto negativo en el empleo como también en el producto. Los ejercicios realizados en este estudio indican que una disminución en el precio internacional de capital robótico en 1\%, en condiciones de altas tasas de sustitución entre empleo y robots, produce una caída en el empleo y los salarios de 0,05\% si el cambio es transitorio y de 0,25\% si es permanente por un aumento en las importaciones de capital robótico.Palabras clave: Automatización; empleo; tecnología; robots; productividad},
number = {1},
urldate = {2022-06-20},
journal = {Revista de análisis económico},
author = {Rivera Taiba, Tiare and Rivera Taiba, Tiare},
month = apr,
year = {2019},
note = {Publisher: ILADES. Universidad Alberto Hurtado.},
pages = {3--49},
file = {Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\L9ZKNTRX\\Rivera Taiba y Rivera Taiba - 2019 - Efectos de la automatización en el empleo en Chile.pdf:application/pdf},
}
@article{wei_autonomous_2015,
title = {Autonomous soil analysis by the {Mars} {Micro}-beam {Raman} {Spectrometer} ({MMRS}) on-board a rover in the {Atacama} {Desert}: a terrestrial test for planetary exploration},
volume = {46},
issn = {1097-4555},
shorttitle = {Autonomous soil analysis by the {Mars} {Micro}-beam {Raman} {Spectrometer} ({MMRS}) on-board a rover in the {Atacama} {Desert}},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jrs.4656},
doi = {10.1002/jrs.4656},
abstract = {Laser Raman spectroscopy (LRS) has been proposed for in situ characterization of molecular species in planetary surface exploration, and three laser Raman spectrometers are included in the science payloads of two under-development missions to Mars (ESA-ExoMars2018 and NASA-Mars2020). We report the first rover test of a laser Raman spectrometer developed for flight, the Mars Micro-beam Raman Spectrometer (MMRS) in the Atacama Desert (Chile). The MMRS was integrated on the Zoë rover and analyzed subsurface samples brought up by a 1 m drill and delivered by a carousel. The MMRS demonstrated robust performance over 50-km traverse on rugged terrains. From MMRS data, igneous minerals, carbonates, sulfates and carbonaceous materials were unambiguously identified. Quantified distributions of major minerals and carbonaceous materials are extracted from MMRS results, which can be used to imply the regional geological evolution, and potential bioactivities. MMRS in the field performed as well as an LRS laboratory instrument when MMRS was focused satisfactorily. The discovery of stable γ-anhydrite, in large quantity (20\% in a sample), in the Atacama soils raises an important question of its stability in the field in a natural environment that is worth further laboratory experimental investigation. Copyright © 2015 John Wiley \& Sons, Ltd.},
language = {en},
number = {10},
urldate = {2022-06-20},
journal = {Journal of Raman Spectroscopy},
author = {Wei, Jie and Wang, Alian and Lambert, James L. and Wettergreen, David and Cabrol, Nathalie and Warren-Rhodes, Kimberley and Zacny, Kris},
year = {2015},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jrs.4656},
keywords = {Atacama Desert, Mars Micro-beam Raman Spectrometer, rover, soil},
pages = {810--821},
file = {Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\TB49FS7Y\\Wei et al. - 2015 - Autonomous soil analysis by the Mars Micro-beam Ra.pdf:application/pdf;Snapshot:C\:\\Users\\cleme\\Zotero\\storage\\WMZF5863\\jrs.html:text/html},
}
@article{laguela_behavior_2018,
title = {Behavior {Analysis} of {Novel} {Wearable} {Indoor} {Mapping} {System} {Based} on {3D}-{SLAM}},
volume = {18},
doi = {10.3390/s18030766},
abstract = {This paper presents a Wearable Prototype for indoor mapping developed by the University of Vigo. The system is based on a Velodyne LiDAR, acquiring points with 16 rays for a simplistic or low-density 3D representation of reality. With this, a Simultaneous Localization and Mapping (3D-SLAM) method is developed for the mapping and generation of 3D point clouds of scenarios deprived from GNSS signal. The quality of the system presented is validated through the comparison with a commercial indoor mapping system, Zeb-Revo, from the company GeoSLAM and with a terrestrial LiDAR, Faro Focus3DX330. The first is considered as a relative reference with other mobile systems and is chosen due to its use of the same principle for mapping: SLAM techniques based on Robot Operating System (ROS), while the second is taken as ground-truth for the determination of the final accuracy of the system regarding reality. Results show that the accuracy of the system is mainly determined by the accuracy of the sensor, with little increment in the error introduced by the mapping algorithm.},
journal = {Sensors},
author = {Lagüela, Susana and Dorado, Iago and Gesto, M. and Arias, Pedro and González-Aguilera, Diego and Lorenzo, Henrique},
month = mar,
year = {2018},
pages = {766},
file = {Texto completo:C\:\\Users\\cleme\\Zotero\\storage\\FBDRQCFV\\Lagüela et al. - 2018 - Behavior Analysis of Novel Wearable Indoor Mapping.pdf:application/pdf},
}
@article{sotelo_robots_2007,
title = {Robots {Móviles}: {Evolución} y {Estado} del {Arte}},
language = {es},
author = {Sotelo, Víctor Ricardo Barrientos and Sánchez, José Rafael García and Ortigoza, Dr Ramón Silva},
year = {2007},
pages = {7},
file = {Sotelo et al. - 2007 - Robots Móviles Evolución y Estado del Arte.pdf:C\:\\Users\\cleme\\Zotero\\storage\\ECHQ9UI2\\Sotelo et al. - 2007 - Robots Móviles Evolución y Estado del Arte.pdf:application/pdf},
}
@book{inves_2004,
address = {Boston, MA},
title = {Investigación aplicada al área de inteligencia artificial y desarrollo de un sistema experto},
language = {es},
urldate = {2022-08-28},
publisher = {Universidad de el Salvador},
author = {Rudy Wilfredo and Hugo Contreras and Ruth Cortez and Danny Gutierrez},
year = {2004},
}
@book{buchanan_2000,
address = {Valencia, ESP},
title = {Ingeniería del conocimiento. De la extracción al modelado de conocimiento},
language = {es},
urldate = {2022-08-30},
publisher = {Revista Iberoamericana de Inteligencia Artificial},
author = {J. T. Palma and E. Paniagua and F. Martín and R. Marín},
year = {2000},
}
@online{area_rob_2017,
author = {Gustavo Hernández Heras},
title = {¿Qué es la robótica? Revista hacia el espacio},
year = 2017,
url = {https://haciaelespacio.aem.gob.mx/revistadigital/articul.php?interior=733},
urldate = {2022-06-07}
}
@article{andres_rosoclingo_2013,
title = {{ROSoClingo}: {A} {ROS} package for {ASP}-based robot control},
shorttitle = {{ROSoClingo}},
abstract = {Knowledge representation and reasoning capacities are vital to cognitive robotics because they provide higher level cognitive functions for reasoning about actions, environments, goals, perception, etc. Although Answer Set Programming (ASP) is well suited for modelling such functions, there was so far no seamless way to use ASP in a robotic environment. We address this shortcoming and show how a recently developed reactive ASP system can be harnessed to provide appropriate reasoning capacities within a robotic system. To be more precise, we furnish a package integrating the reactive ASP solver oClingo with the popular open-source robotic middleware ROS. The resulting system, ROSoClingo, provides a generic way by which an ASP program can be used to control the behaviour of a robot and to respond to the results of the robot's actions.},
author = {Andres, Benjamin and Obermeier, Philipp and Sabuncu, Orkunt and Schaub, Torsten and Rajaratnam, David},
month = jul,
year = {2013},
file = {Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\NAN3CNII\\Andres et al. - 2013 - ROSoClingo A ROS package for ASP-based robot cont.pdf:application/pdf},
}
@online{robin_robotics_2019,
author = {Robinroy Peter},
title = {ROS Topics: ROS Tutorial},
year = 2019,
url = {https://robinrobotic.blogspot.com/2019/07/ros-topics-ros-tutorial.html},
urldate = {2022-06-07}
}
@online{ros_services_2018,
author = {Raymond Chen},
title = {ROS Services: Writing and Listening},
year = 2018,
url = {https://medium.com/@raymonduchen/ros-\%E6\%87\%B6\%E4\%BA\%BA\%E7\%AD\%86\%E8\%A8\%98-4-\%E4\%BB\%A5c-\%E6\%92\%B0\%E5\%AF\%ABservice\%E8\%88\%87client-1f5fa3184c60},
urldate = {2022-06-07}
}
@inproceedings{kohlbrecher_flexible_2011,
title = {A flexible and scalable {SLAM} system with full {3D} motion estimation},
doi = {10.1109/SSRR.2011.6106777},
abstract = {For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing. By using a fast approximation of map gradients and a multi-resolution grid, reliable localization and mapping capabilities in a variety of challenging environments are realized. Multiple datasets showing the applicability in an embedded hand-held mapping system are provided. We show that the system is sufficiently accurate as to not require explicit loop closing techniques in the considered scenarios. The software is available as an open source package for ROS.},
booktitle = {2011 {IEEE} {International} {Symposium} on {Safety}, {Security}, and {Rescue} {Robotics}},
author = {Kohlbrecher, Stefan and von Stryk, Oskar and Meyer, Johannes and Klingauf, Uwe},
month = nov,
year = {2011},
note = {ISSN: 2374-3247},
keywords = {Equations, Inertial Navigation, Laser radar, Navigation, Robust and Fast Localization, Simultaneous localization and mapping, Simultaneous Localization and Mapping, Three dimensional displays},
pages = {155--160},
file = {IEEE Xplore Abstract Record:C\:\\Users\\cleme\\Zotero\\storage\\RMGHWZGA\\6106777.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\CK5KHRZM\\Kohlbrecher et al. - 2011 - A flexible and scalable SLAM system with full 3D m.pdf:application/pdf},
}
@article{vSlam_takafumi_2017,
author = {Takafumi Taketomi and Hideaku Uchimaya and Sei Ikeda},
title = {Visual SLAM algorithms: a survey from 2010 to 2016},
language = {en},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2017},
pages = {11},
file = {Sotelo et al. - 2007 - Robots Móviles Evolución y Estado del Arte.pdf:C\:\\Users\\cleme\\Zotero\\storage\\ECHQ9UI2\\Sotelo et al. - 2007 - Robots Móviles Evolución y Estado del Arte.pdf:application/pdf},
}
@ARTICLE{4160954,
author={Davison, Andrew J. and Reid, Ian D. and Molton, Nicholas D. and Stasse, Olivier},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={MonoSLAM: Real-Time Single Camera SLAM},
year={2007},
volume={29},
number={6},
pages={1052-1067},
doi={10.1109/TPAMI.2007.1049}}
@ARTICLE{vslam_2018,
author={Jonathan Piat and Philippe Fillatreau and Daniel Trotei and Francois Brenot and Michel Devy},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={HW/SW co-design of a visual SLAM application},
year={2018},
volume={17},
number={6},
pages={667-689},
doi={https://doi.org/10.1007/s11554-018-0836-2}}
@ARTICLE{3dslam_2018,
author={Jan Weingarten},
journal={Lausanne, EPFL},
title={Feature-based 3D SLAM},
year={2006},
pages={137},
doi={10.5075/epfl-thesis-3601}}
@ARTICLE{ros_package1_2018,
author={Li Zhi and Mei Xuesong},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Navigation and Control System of Mobile Robot Based on ROS},
year={2018},
pages={5},
doi={10.1109/IAEAC.2018.8577901}}
@ARTICLE{ros_package2_2018,
author={Young Li and Changxing Shi},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Localization and Navigation for Indoor Mobile Robot Based on ROS},
year={2018},
pages={5},
doi={10.1109/CAC.2018.8623225}}
@inproceedings{omara_indoor_2015,
title = {Indoor mapping using kinect and {ROS}},
doi = {10.1109/ISAMSR.2015.7379780},
abstract = {This research covers an endeavor by the author on the usage of automated vision and navigation framework; the research is conducted by utilizing a Kinect sensor requiring minimal effort framework for exploration purposes in the zone of robot route. For this framework, GMapping (a highly efficient Rao-Blackwellized particle filer to learn grid maps from laser range data) parameters have been optimized to improve the accuracy of the map generation and the laser scan. With the use of Robot Operating System (ROS), the open source GMapping bundle was utilized as a premise for a map era and Simultaneous Localization and Mapping (SLAM). Out of the many different map generation techniques, the tele-operation used is interactive marker, which controls the TurtleBot 2 movements via RVIZ (3D visualization tool for ROS). Test results completed with the multipurpose robot in a counterfeit and regular environment represents the preferences of the proposed strategy. From experiments, it is found that Kinect sensor produces a more accurate map compared to non-filtered laser range finder data, which is excellent since the price of a Kinect sensor is much cheaper than a laser range finder. An expansion of experimental results was likewise done to test the performance of the portable robot frontier exploring in an obscure environment while performing SLAM alongside the proposed technique.},
booktitle = {2015 {International} {Symposium} on {Agents}, {Multi}-{Agent} {Systems} and {Robotics} ({ISAMSR})},
author = {Omara, Hesham Ibrahim Mohamed Ahmed and Sahari, Khairul Salleh Mohamed},
month = aug,
year = {2015},
keywords = {Cameras, Kinect, Simultaneous localization and mapping, SLAM, Mobile robots, ROS, Navigation, Gmapping, frontier exploration, Interactive marker, Multi-agent systems, TurtleBot 2},
pages = {110--116},
file = {IEEE Xplore Full Text PDF:C\:\\Users\\cleme\\Zotero\\storage\\ZLIDQFCU\\Omara y Sahari - 2015 - Indoor mapping using kinect and ROS.pdf:application/pdf},
}
@article{taheri_slam_2021,
title = {{SLAM}; definition and evolution},
volume = {97},
issn = {09521976},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0952197620303092},
doi = {10.1016/j.engappai.2020.104032},
language = {en},
urldate = {2022-11-07},
journal = {Engineering Applications of Artificial Intelligence},
author = {Taheri, Hamid and Xia, Zhao Chun},
month = jan,
year = {2021},
pages = {104032},
file = {Taheri y Xia - 2021 - SLAM\; definition and evolution.pdf:C\:\\Users\\cleme\\Zotero\\storage\\6Z7ZWKDR\\Taheri y Xia - 2021 - SLAM\; definition and evolution.pdf:application/pdf},
}
@article{li_topology_2016,
author = {Li, Li-juan and Shao, Zeng-zhen and Chen, Shou-yuan and Liu, Zheng-qiang and Yan, Peng-chao},
title = {The topology design and performance analysis of sound-driving system on airport},
journal = {International Journal of Collaborative Intelligence},
volume = {1},
number = {3},
pages = {237-246},
year = {2016},
doi = {10.1504/IJCI.2016.077105},
note ={PMID: 77105},
URL = {
https://www.inderscienceonline.com/doi/abs/10.1504/IJCI.2016.077105
},
eprint = {https://www.inderscienceonline.com/doi/pdf/10.1504/IJCI.2016.077105
}
,
abstract = { This paper proposes an intelligent network topology of sound-driving system on airport in order to solve the bird-striking problem. At first, the bird-striking system existing now has several problems, such as the points covered by signal are less and the transmission of signal is unstable. To solve the problems, the article proposed a network design which mix RS485 and ZigBee. Then based on the comprehensive considering, it determines the network topology and network protocol of the system. Finally, it analysis the performance of the system through the actual operation: good stability, no blind signal coverage, enabling the audience to control. }
}
@inproceedings{klein_parallel_2007,
address = {Nara, Japan},
title = {Parallel {Tracking} and {Mapping} for {Small} {AR} {Workspaces}},
isbn = {978-1-4244-1749-0},
url = {http://ieeexplore.ieee.org/document/4538852/},
doi = {10.1109/ISMAR.2007.4538852},
urldate = {2022-11-07},
booktitle = {2007 6th {IEEE} and {ACM} {International} {Symposium} on {Mixed} and {Augmented} {Reality}},
publisher = {IEEE},
author = {Klein, Georg and Murray, David},
month = nov,
year = {2007},
pages = {1--10},
file = {Klein y Murray - 2007 - Parallel Tracking and Mapping for Small AR Workspa.pdf:C\:\\Users\\cleme\\Zotero\\storage\\V2EYTAIZ\\Klein y Murray - 2007 - Parallel Tracking and Mapping for Small AR Workspa.pdf:application/pdf},
}
@book{john_sonar_1992,
address = {New York, NY},
title = {Directed Sonar Sensing for Mobile Robot Navigation},
isbn = {978-0-7923-9242-2},
url = {https://link.springer.com/book/10.1007/978-1-4615-3652-9},
language = {en},
publisher = {Springer US},
author = {John J. Leonard and Hugh F. Durrant-Whyte},
year = {1992},
doi = {https://doi.org/10.1007/978-1-4615-3652-9},
}
@INPROCEEDINGS{7482163,
author={Khairuddin, Alif Ridzuan and Talib, Mohamad Shukor and Haron, Habibollah},
booktitle={2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)},
title={Review on simultaneous localization and mapping (SLAM)},
year={2015},
volume={},
number={},
pages={85-90},
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file = {Versión aceptada:C\:\\Users\\cleme\\Zotero\\storage\\AB9XXBDP\\Durrant-Whyte y Bailey - 2006 - Simultaneous localization and mapping part I.pdf:application/pdf},
}
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author={Yavuz, Sirma and Kurt, Zeyneb and Bicer, M. Serdar},
booktitle={2009 IEEE 17th Signal Processing and Communications Applications Conference},
title={Simultaneous localization and mapping using Extended Kalman Filter},
year={2009},
volume={},
number={},
pages={700-703},
doi={10.1109/SIU.2009.5136492}}
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issn = {0924-4247},
url = {https://www.sciencedirect.com/science/article/pii/092442479085003M},
doi = {https://doi.org/10.1016/0924-4247(90)85003-M},
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annote = {Proceedings of the 5th International Conference on Solid-State Sensors and Actuators and Eurosensors III},
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title={Power-SLAM: A linear-complexity, consistent algorithm for SLAM},
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