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Sobre la mejora esperada de la estimación de la odometría en Exploración Integrada

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Sobre la mejora esperada de la estimación de la odometría en Exploración Integrada

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dc.contributor.author Toriz Palacios, A. es_ES
dc.contributor.author Sánchez López, A. es_ES
dc.date.accessioned 2020-05-12T18:03:42Z
dc.date.available 2020-05-12T18:03:42Z
dc.date.issued 2020-04-07
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/142980
dc.description.abstract [EN] The problem of Integrated Exploration is the new trend in the construction of maps of unknown environments; in it, the old paradigm of Simultaneous Localization and Mapping (SLAM) is integrated with the planning of movements necessary for this task to be performed autonomously. However, although motion control is an essential part of this new paradigm, the existing literature has been limited to developing strategies that improve travel times and environmental coverage, leaving aside the impact that these can have on robot odometry and, consequently, on the requirements of localization algorithms. Accordingly, this document presents a new efficient way of exploring environments for the SLAM problem, which aims to improve exploration times and maximize coverage of the work area, as well as minimize the accumulated odometric error to simplify the localization process. es_ES
dc.description.abstract [ES] El problema de Exploración integrada es la nueva tendencia en la construcción de mapas de ambientes desconocidos; en ella, se integra el viejo paradigma de la localización y mapeo simultáneos (SLAM) con la planificación de movimientos necesarios, para que esta tarea sea realizada de forma autónoma. Sin embargo, aunque el control de movimientos es una parte esencial de este paradigma, los trabajos encontrados en la literatura se han limitado a desarrollar estrategias que mejoren los tiempos de recorridos y la cobertura del ambiente, dejado de lado el impacto que estos puede tener sobre la odometría del robot y, en consecuencia, sobre los requerimientos de los algoritmos de localización. De lo anterior, en este documento se presenta una nueva forma eficiente de exploración de ambientes para el problema de SLAM, que tiene como objetivo mejorar los tiempos de exploración y maximizar la cobertura del área de trabajo, pero además el de minimizar el error odométrico acumulado para simplificar el proceso de localización. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Autonomous mobile robot es_ES
dc.subject Path planning es_ES
dc.subject Motion estimation es_ES
dc.subject Position errors es_ES
dc.subject Error rates es_ES
dc.subject Robot móvil autónomo es_ES
dc.subject Planificación de rutas es_ES
dc.subject Estimación de movimiento es_ES
dc.subject Errores de posición odométrica es_ES
dc.subject Tasa de error es_ES
dc.title Sobre la mejora esperada de la estimación de la odometría en Exploración Integrada es_ES
dc.title.alternative On the expected improvement of odometry estimation in integrated exploration es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2019.11828
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Toriz Palacios, A.; Sánchez López, A. (2020). Sobre la mejora esperada de la estimación de la odometría en Exploración Integrada. Revista Iberoamericana de Automática e Informática industrial. 17(2):229-238. https://doi.org/10.4995/riai.2019.11828 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2019.11828 es_ES
dc.description.upvformatpinicio 229 es_ES
dc.description.upvformatpfin 238 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\11828 es_ES
dc.description.references Abbas, T., Arif, M., Ahmed, W., 2006. Measurement and correction of systematic odometry errors caused by kinematics imperfections in mobile robots. SICE-ICASE International Joint Conference, 2073-2078. https://doi.org/10.1109/SICE.2006.315554 es_ES
dc.description.references Borenstein, J., 1998. Experimental results from internal odometry error correction with the OmniMate mobile robot. IEEE Transactions on Robotics and Automation, 14(6), 963-969. https://doi.org/10.1109/70.736779 es_ES
dc.description.references Brossard, M., Bonnabel, S., 2018. Learning Wheel Odometry and IMU Errors for Localization. IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/ICRA.2019.8794237 es_ES
dc.description.references Burgard, W., Moors, M., Stachniss, C., Schneider, F. E., 2005. Coordinated multi-robot exploration. IEEE Transactions on robotics, 21(3), 376-386. https://doi.org/10.1109/TRO.2004.839232 es_ES
dc.description.references Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Leonard, J. J., 2016. Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age. IEEE Transactions on robotics, 32(6), 1309-1332. https://doi.org/10.1109/TRO.2016.2624754 es_ES
dc.description.references Campos, F. M., Marques, M., Carreira, F., Calado, J. M. F., 2017. A complete frontier-based exploration method for Pose-SLAM. IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 79-84. https://doi.org/10.1109/ICARSC.2017.7964056 es_ES
dc.description.references Chen, N. Y., Shaw, J., Lin, H. I., 2017. Exploration method improvements of autonomous robot for a 2-D environment navigation. Journal of Marine Science and Technology, 25(1), 34-42. http://dx.doi.org/10.6119/2fJMST-016-0719-1 es_ES
dc.description.references Franchi, A., Freda, L., Oriolo, G., Vendittelli, M., 2007. A randomized strategy for cooperative robot exploration. IEEE International Conference on Robotics and Automation, 768-774. https://doi.org/10.1109/ROBOT.2007.363079 es_ES
dc.description.references Franchi, A., Freda, L., Oriolo, G., Vendittelli, M., 2009. The sensor-based random graph method for cooperative robot exploration. IEEE/ASME Transactions on Mechatronics, 14(2), 163-175. https://doi.org/10.1109/TMECH.2009.2013617 es_ES
dc.description.references Freda, L., Loiudice, F., Oriolo, G., 2006. A randomized method for integrated exploration. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2457-2464. https://doi.org/10.1109/IROS.2006.281689 es_ES
dc.description.references Gil, A., Juliá, M., Reinoso, Ó., 2015. Occupancy grid based graph-SLAM using the distance transform, SURF features and SGD. Engineering Applications of Artificial Intelligence, 40, 1-10. https://doi.org/10.1016/j.engappai.2014.12.010 es_ES
dc.description.references Hähnel, D., Thrun, S., Wegbreit, B., Burgard, W., 2005. Towards lazy data association in SLAM. Eleventh International Symposium Robotics Research, 421-431. https://doi.org/10.1007/11008941_45 es_ES
dc.description.references Hanif, M. S., Bilal, M., Munawar, K., Balamash, A. S., 2018. Implementation of an Embedded Testbed for Indoor SLAM. In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA), 1-8. https://doi.org/10.1109/AICCSA.2018.8612782 es_ES
dc.description.references Hidalgo-Carrió, J., Hennes, D., Schwendner, J., Kirchner, F., 2017. Gaussian process estimation of odometry errors for localization and mapping. In 2017 IEEE International Conference on Robotics and Automation (ICRA), 5696-5701. https://doi.org/10.1109/ICRA.2017.7989670 es_ES
dc.description.references Holz, D., Basilico, N., Amigoni, F., Behnke, S., 2010. Evaluating the efficiency of frontier-based exploration strategies. In ISR 2010 (41st International Symposium on Robotics) and ROBOTIK 2010 (6th German Conference on Robotics), 1-8. es_ES
dc.description.references Jin, J., Chung, W., 2019. Obstacle Avoidance of Two-Wheel Differential Robots Considering the Uncertainty of Robot Motion on the Basis of Encoder Odometry Information. Sensors, 19(2), 289-299. https://doi.org/10.3390/s19020289 es_ES
dc.description.references Juliá, M., Gil, A., Payá, L., Reinoso, O., 2008. Local minima detection in potential field based cooperative multirobot exploration. International Journal of Factory Automation, Robotics and Soft Computing, 3. es_ES
dc.description.references Lamon, P., Siegwart, R., 2007. 3D position tracking in challenging terrain. The International Journal of Robotics Research, 26(2), 167-186. https://doi.org/10.1007/978-3-540-33453-8_44 es_ES
dc.description.references Lou, Q., González, F., Kövecses, J., 2019. Kinematic Modeling and State Estimation of Exploration Rovers. IEEE Robotics and Automation Letters, 4(2), 1311-1318. https://doi.org/10.1109/LRA.2019.2895393 es_ES
dc.description.references Maddahi, Y., Sepehri, N., Maddahi, A., Abdolmohammadi, M., 2012. Calibration of wheeled mobile robots with differential drive mechanisms: An experimental approach. Robotica. 30(6). https://doi.org/10.1017/S0263574711001329 es_ES
dc.description.references Maddahi, Y., 2018. Off-Line Calibration of Autonomous Wheeled Mobile Robots. In Handbook of Research on Biomimetics and Biomedical Robotics, 375-389. https://doi.org/10.4018/978-1-5225-2993-4.ch016 es_ES
dc.description.references Ojeda, L., Borenstein, J., 2004. Methods for the reduction of odometry errors in over-constrained mobile robots. Autonomous Robots, 16(3), 273-286. https://doi.org/10.1023/B:AURO.0000025791.45313.01 es_ES
dc.description.references Prieto, R. A., Cuadra-Troncoso, J. M., Álvarez-Sánchez, J. R., Santosjuanes, I. N., 2013. Reactive Navigation and Online SLAM in Autonomous Frontier-Based Exploration. In International Work-Conference on the Interplay Between Natural and Artificial Computation, 45-55. https://doi.org/10.1007/978-3-642-38622-0_5 es_ES
dc.description.references Romero, L., Morales, E. F., Sucar, L. E., 2002. An exploration approach for indoor mobile robots reducing odometric errors. In Mexican International Conference on Artificial Intelligence, 51-60. https://doi.org/10.1007/3-540-46016-0_6 es_ES
dc.description.references Toriz P, A., Sánchez L, A., Bedolla Cordero, J. M. E., 2017. The random exploration graph for optimal exploration of unknown environments. International Journal of Advanced Robotic Systems, 14(1). https://doi.org/10.1177/1729881416687110 es_ES
dc.description.references Torres-González, A., Martinez-de Dios, J., Ollero, A., 2014. An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements. Sensors, 14(5), 7684-7710. DOI: 10.3390/s140507684 https://doi.org/10.3390/s140507684 es_ES
dc.description.references Yu, N., Wang, S., 2019. Enhanced Autonomous Exploration and Mapping of an Unknown Environment with the Fusion of Dual RGB-D Sensors. Engineering, 5(1), 164-172. https://doi.org/10.1016/j.eng.2018.11.014 es_ES


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