VEHÍCULOS TERRESTRES NO TRIPULADOS, SUS APLICACIONES Y TECNOLOGÍAS DE IMPLEMENTACIÓN
DOI:
https://doi.org/10.18041/1909-2458/ingeniare.30.7925Palabras clave:
Vehículos terrestres no tripulados, aplicaciones en la industria, tendencias tecnológicas, Tree of Science, Revisión SistemáticaResumen
Los vehículos terrestres no tripulados son considerados máquinas semi autónomas o autónomas que realizan operaciones complejas de transporte y monitoreo de variables físicas y ambientales; por mencionar algunas. Estos vehículos permiten personalizar, optimizar y dar flexibilidad a las demandas y desafíos de innovación en múltiples campos de aplicación en la industria como cartografía, agricultura, seguridad, minería, telemetría, militar, geociencia, ambiental y logística; por tanto, creemos que consolidar la información científica publicada alrededor de este tema permite a los lectores comprender las conexiones entre los diferentes enfoques, aplicaciones y tecnologías habilitadoras para determinar el rumbo al cual desean llevar su investigación; y, al mismo tiempo, promover más debates sobre la fusión de la robótica móvil en las aplicaciones de internet de las cosas que están emergiendo en la industrial actual. En este artículo se implementó la herramienta web “Tree of Science” y la Revisión Sistemática para el análisis de la información.
Descargas
Referencias
J. Wang, Z. Jiang, Q. Song, and Z. Zhou, “Forward looking InSAR based field terrain mapping for unmanned ground vehicle,” in Proceedings of 2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016, Aug. 2016, pp. 168–173, doi: 10.1109/ACIRS.2016.7556207.
D. Rammoorthy, K. K. Radhakrishnan, and S. Ramesh, “Algorithm for threat area avoidance in military unmanned ground vehicles,” in Advanced Materials Research, Nov. 2012, vol. 403–408, pp. 4456–4461, doi: 10.4028/www.scientific.net/AMR.403-408.4456.
O. Y. Agunbiade, S. M. Ngwira, T. Zuva, and Y. Akanbi, “Improving ground detection for unmanned vehicle systems in environmental noise scenarios,” Int. J. Adv. Manuf. Technol., vol. 84, no. 9–12, pp. 2719–2727, Jun. 2016, doi: 10.1007/s00170-015-8109-8.
A. Nüchter, K. Lingemann, J. Hertzberg, and H. Surmann, “6D SLAM—3D mapping outdoor environments,” J. F. Robot., vol. 24, no. 8–9, pp. 699–722, Sep. 2007, doi: 10.1002/rob.20209.
J. S. Botero-Valencia and E. Delgado-Trejos, “Localización y orientación de equipos móviles usando color,” TecnoLógicas, vol. 23, p. 148, Dec. 2009, doi: 10.22430/22565337.243.
A. Ruiz-Larrea, J. J. Roldán, M. Garzón, J. Del Cerro, and A. Barrientos, “A UGV approach to measure the ground properties of greenhouses,” in Advances in Intelligent Systems and Computing, 2016, vol. 418, pp. 3–13, doi: 10.1007/978-3-319-27149-1_1.
J. E. Naranjo, F. Jimenez, M. Anguita, and J. L. Rivera, “Automation kit for Dual-Mode military unmanned ground vehicle for surveillance missions,” IEEE Intell. Transp. Syst. Mag., pp. 2–15, 2018, doi: 10.1109/MITS.2018.2880274.
K. A. Ghamry, M. A. Kamel, and Y. Zhang, “Cooperative forest monitoring and fire detection using a team of UAVs-UGVs,” in 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016, Jun. 2016, pp. 1206–1211, doi: 10.1109/ICUAS.2016.7502585.
J. Alberts, D. Edwards, T. Soule, M. Anderson, and M. O’Rourke, “Autonomous navigation of an unmanned ground vehicle in unstructured forest terrain,” in Proceedings of the 2008 ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems, LAB-RS 2008, Aug. 2008, pp. 103–108, doi: 10.1109/LAB-RS.2008.25.
S. Hutangkabodee, Y. H. Zweiri, L. D. Seneviratne, and K. Althoefer, “Traversability prediction for unmanned ground vehicles based on identified soil parameters,” IFAC Proc. Vol., vol. 38, no. 1, pp. 25–30, Jan. 2005, doi: 10.3182/20050703-6-cz-1902.02056.
S. Serna, “Desarrollo de un robot interactivo para la distribución de información,” TecnoLógicas, vol. 18, p. 170, Jun. 2007, doi: 10.22430/22565337.481.
S. Bonadies, A. Lefcourt, and S. A. Gadsden, “A survey of unmanned ground vehicles with applications to agricultural and environmental sensing,” in Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, May 2016, vol. 9866, p. 98660Q, doi: 10.1117/12.2224248.
I. Schiff, “New guidelines for review articles,” Menopause, vol. 26, no. 12, pp. 1357–1360, Dec. 2019, doi: 10.1097/GME.0000000000001469.
D. Moher et al., “Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement,” PLoS Med., vol. 6, no. 7, pp. 264–269, Jul. 2009, doi: 10.1371/journal.pmed.1000097.
G. P. Maestre Góngora, “Revisión de literatura sobre ciudades inteligentes: una perspectiva centrada en las TIC,” INGENIARE, vol. 11, no. 19, p. 137, Jul. 2015, doi: 10.18041/1909-2458/ingeniare.19.531.
C. Manterola, P. Astudillo, E. Arias, and N. Claros, “Systematic reviews of the literature: what should be known about them,” Cirugía Española (English Ed., vol. 91, no. 3, pp. 149–155, Mar. 2013, doi: 10.1016/j.cireng.2013.07.003.
R. Vínculos, G. Osorio, and C. Lopez, “Networking en pequeña empresa: una revisión bibliográfica utilizando la teoría de grafos,” Netw. EN PEQUEÑA Empres. UNA REVISIÓN BIBLIOGRÁFICA Util. LA Teor. GRAFOS, vol. 11, no. 2, pp. 6–16, Dec. 2014, doi: 10.14483/2322939X.9664.
C. M. Botero, O. Cervantes, and C. W. Finkl, “State of the art beach environmental quality from the tree of science platform,” Coast. Res. Libr., vol. 24, pp. 781–793, Dec. 2017, doi: 10.1007/978-3-319-58304-4_39.
S. Robledo-Giraldo, N. D. Duque-Méndez, and J. I. Zuluaga-Giraldo, “Difusión de productos a través de redes sociales: una revisión bibliográfica utilizando la teoría de grafos,” Respuestas, vol. 18, no. 2, pp. 28–42, Jul. 2013, doi: 10.22463/0122820x.361.
V. Ramírez Valencia, S. Ruiz Herrera, and O. D. Castrillón Gómez, “Algoritmos aplicados en la programación de las cadenas de suministros para minimizar costos. Revisión de literatura*,” INGENIARE, vol. 12, no. 20, p. 121, Dec. 2016, doi: 10.18041/1909-2458/ingeniare.20.414.
R. A. Brooks, “A robust layered control system for a mobile robot,” IEEE J. Robot. Autom., vol. 2, no. 1, pp. 14–23, Mar. 1986, doi: 10.1109/JRA.1986.1087032.
M. W. M. Gamini Dissanayake, P. Newman, S. Clark, H. F. Durrant-Whyte, and M. Csorba, “A solution to the simultaneous localization and map building (SLAM) problem,” IEEE Trans. Robot. Autom., vol. 17, no. 3, pp. 229–241, Jun. 2001, doi: 10.1109/70.938381.
N. A. Olmedo and M. G. Lipsett, “Design and field experimentation of a robotic system for tailings characterization,” J. Unmanned Veh. Syst., vol. 4, no. 3, pp. 169–192, Sep. 2016, doi: 10.1139/juvs-2015-0034.
S. Shimoda, Y. Kuroda, and K. Iagnemma, “High-speed navigation of unmanned ground vehicles on uneven terrain using potential fields,” Robotica, vol. 25, no. 4, pp. 409–424, Jul. 2007, doi: 10.1017/S0263574706003171.
S. Zaman, L. Comba, A. Biglia, D. Ricauda Aimonino, P. Barge, and P. Gay, “Cost-effective visual odometry system for vehicle motion control in agricultural environments,” Comput. Electron. Agric., vol. 162, pp. 82–94, Jul. 2019, doi: 10.1016/j.compag.2019.03.037.
S. Nithin, B. Madhevan, R. Ghosh, G. V. P. Bharat Kumar, and N. K. Philip, “Prediction of mechanical soil properties based on experimental and computational model of a rocker bogie rover,” in Advances in Intelligent Systems and Computing, 2017, vol. 517, pp. 199–210, doi: 10.1007/978-981-10-3174-8_18.
E. Vaeljaots, H. Lehiste, M. Kiik, and T. Leemet, “Soil sampling automation case-study using unmanned ground vehicle,” in Engineering for Rural Development, 2018, vol. 17, pp. 982–987, doi: 10.22616/ERDev2018.17.N503.
P. M. Cao, E. L. Hall, and E. Zhang, “Soil sampling sensor system on a mobile robot,” in Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, Oct. 2003, vol. 5267, p. 310, doi: 10.1117/12.516367.
J. P. Fentanes, I. Gould, T. Duckett, S. Pearson, and G. Cielniak, “3-D soil compaction mapping through kriging-based exploration with a mobile robot,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3066–3072, Oct. 2018, doi: 10.1109/LRA.2018.2849567.
M. Pierzchała, P. Giguère, and R. Astrup, “Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM,” Comput. Electron. Agric., vol. 145, pp. 217–225, Feb. 2018, doi: 10.1016/j.compag.2017.12.034.
K. Tanaka et al., “A study on path planning for small mobile robot to move in forest area,” in 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017, Mar. 2018, vol. 2018-Janua, pp. 2167–2172, doi: 10.1109/ROBIO.2017.8324740.
H. Zhang, X. Dai, F. Sun, and J. Yuan, “Terrain classification in field environment based on random forest for the mobile robot,” in Chinese Control Conference, CCC, Aug. 2016, vol. 2016-Augus, pp. 6074–6079, doi: 10.1109/ChiCC.2016.7554310.
Dhanalakshmi and A. E. S. Leni, “Instance vehicle monitoring and tracking with internet of things using Arduino,” Int. J. Smart Sens. Intell. Syst., vol. 10, no. Specialissue, pp. 123–135, Sep. 2017, doi: 10.21307/ijssis-2017-240.
A. Roberts and A. Pecka, “4G Network performance analysis for real-time telemetry data transmitting to mobile agricultural robot,” in Engineering for Rural Development, May 2018, vol. 17, pp. 1501–1506, doi: 10.22616/ERDev2018.17.N362.
J. Gomes, F. Marques, A. Lourenço, R. Mendonça, P. Santana, and J. Barata, “Gaze-directed telemetry in high latency wireless communications: the case of robot teleoperation,” in IECON Proceedings (Industrial Electronics Conference), Dec. 2016, pp. 704–709, doi: 10.1109/IECON.2016.7792996.
A. Wendel, J. Underwood, and K. Walsh, “Maturity estimation of mangoes using hyperspectral imaging from a ground based mobile platform,” Comput. Electron. Agric., vol. 155, pp. 298–313, Dec. 2018, doi: 10.1016/j.compag.2018.10.021.
E. Zampetti et al., “Remotely controlled terrestrial vehicle integrated sensory system for environmental monitoring,” in Lecture Notes in Electrical Engineering, 2018, vol. 431, pp. 338–343, doi: 10.1007/978-3-319-55077-0_43.
K. Bin Hasnan, L. B. Saesar, M. S. Ikhmatiar, and T. Herawan, “JOMS: System architecture for telemetry and visualization on unmanned vehicle,” in Procedia Engineering, 2012, vol. 29, pp. 3899–3903, doi: 10.1016/j.proeng.2012.01.591.
P. Liu, T. Fu, J. Xu, and Y. Ding, “Efficient data collection in widely distributed wireless sensor networks with time window and precedence constraints,” Sensors, vol. 17, no. 2, p. 421, Feb. 2017, doi: 10.3390/s17020421.
P. Novák, J. Babjak, T. Kot, P. Olivka, and W. Moczulski, “Exploration mobile robot for coal mines,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9055, pp. 209–215, doi: 10.1007/978-3-319-22383-4_16.
D. Ghosh, B. Samanta, and D. Chakravarty, “Multi sensor data fusion for 6D pose estimation and 3D underground mine mapping using autonomous mobile robot,” Int. J. Image Data Fusion, vol. 8, no. 2, pp. 173–187, Apr. 2017, doi: 10.1080/19479832.2016.1226966.
P. Novák, T. Kot, J. Babjak, Z. Konečný, W. Moczulski, and Á. Rodriguez López, “Implementation of explosion safety regulations in design of a mobile tobot for coal mines,” Appl. Sci., vol. 8, no. 11, p. 2300, Nov. 2018, doi: 10.3390/app8112300.
T. Kot, P. Novák, J. Babjak, and P. Olivka, “Rendering of 3D maps with additional information for operator of a coal mine mobile robot,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9991 LNCS, pp. 214–225, doi: 10.1007/978-3-319-47605-6_18.
C. A. James, T. P. Bednarz, K. Haustein, L. Alem, C. Caris, and A. Castleden, “Teleoperation of a mobile mining robot using a panoramic display: An exploration of operators sense of presence,” in IEEE International Conference on Automation Science and Engineering, 2011, pp. 279–284, doi: 10.1109/CASE.2011.6042427.
M. Yagimli and H. S. Varol, “Mine detecting GPS-based unmanned ground vehicle,” in 2009 4th International Conference on Recent Advances in Space Technologies, Jun. 2009, pp. 303–306, doi: 10.1109/RAST.2009.5158216.
Y. Liu, Z. Luo, Z. Liu, J. Shi, and G. Cheng, “Cooperative routing problem for ground vehicle and unmanned aerial vehicle: the application on intelligence, surveillance, and reconnaissance missions,” IEEE Access, vol. 7, pp. 63504–63518, 2019, doi: 10.1109/ACCESS.2019.2914352.
B. Shoop, M. Johnston, R. Goehring, J. Moneyhun, and B. Skibba, “Mobile detection assessment and response systems (MDARS): a force protection physical security operational success,” in Unmanned Systems Technology VIII, May 2006, vol. 6230, p. 62301Y, doi: 10.1117/12.665939.
S. Barbe, J.-C. Krapez, and Y. Louvet, “Performance modeling and assessment of infrared-sensors applicable for TALOS project UGV as a function of target/background and environmental conditions,” in Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIII, May 2012, vol. 8355, p. 83551A, doi: 10.1117/12.918564.
S. Yu, C. Choi, S. Lee, J. Lee, and C. Han, “Development of an articulated mine-detecting manipulator system for mobile robots,” J. Mech. Sci. Technol., vol. 25, no. 4, pp. 1051–1060, Apr. 2011, doi: 10.1007/s12206-011-0211-8.
M. Seder et al., “Open platform based mobile robot control for automation in manufacturing logistics,” in IFAC-PapersOnLine, Oct. 2019, vol. 52, no. 22, pp. 95–100, doi: 10.1016/j.ifacol.2019.11.055.
D. Zeng, G. Xu, J. Zhong, and L. Li, “Development of a mobile platform for security robot,” in Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2007, 2007, pp. 1262–1267, doi: 10.1109/ICAL.2007.4338763.
M. Saitoh, Y. Takahashi, A. Sankaranarayanan, H. Ohmachi, and K. Marukawa, “Mobile robot testbed with manipulator for security guard application,” in Proceedings - IEEE International Conference on Robotics and Automation, 1995, vol. 3, pp. 2518–2523, doi: 10.1109/robot.1995.525637.
L. Y. Chung, “Remote teleoperated and autonomous mobile security robot development in ship environment,” Math. Probl. Eng., vol. 2013, pp. 1–14, 2013, doi: 10.1155/2013/902013.
Y. Shimosasa et al., “Security service system using autonomous mobile robot,” in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1999, vol. 4, pp. 825–829, doi: 10.1109/icsmc.1999.812514.
G. K. Dey, R. Hossen, M. S. Noor, and K. T. Ahmmed, “Distance controlled rescue and security mobile robot,” in 2013 International Conference on Informatics, Electronics and Vision, ICIEV 2013, Aug. 2013, pp. 1–6, doi: 10.1109/ICIEV.2013.6572602.
R. C. Luo, P. K. Wang, Y. F. Tseng, and T. Y. Lin, “Navigation and mobile security system of home security robot,” in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2006, vol. 1, pp. 169–174, doi: 10.1109/ICSMC.2006.384377.
M. F. R. Lee, N. T. Hung, and F. H. S. Chiu, “An autonomous mobile robot for indoor security patrol,” in iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications, 2013, pp. 189–194, doi: 10.1109/iFuzzy.2013.6825434.
P. M. L. Lapeña, J. I. Q. Blanco, K. I. Bunda, A. G. S. Cruz, A. I. Ramirez, and A. A. Bandala, “Swarm algorithm implementation in mobile robots for security and surveillance,” in IEEE Region 10 Annual International Conference, Proceedings/TENCON, Jan. 2015, vol. 2015-Janua, pp. 1–5, doi: 10.1109/TENCON.2014.7022413.
J.-F. Lalonde, N. Vandapel, D. F. Huber, and M. Hebert, “Natural terrain classification using three-dimensional ladar data for ground robot mobility,” J. F. Robot., vol. 23, no. 10, pp. 839–861, Oct. 2006, doi: 10.1002/rob.20134.
D. Martinez et al., “Ambient intelligence application based on environmental measurements performed with an assistant mobile robot,” Sensors (Switzerland), vol. 14, no. 4, pp. 6045–6055, Mar. 2014, doi: 10.3390/s140406045.
J. Wu et al., “An intelligent environmental monitoring system based on autonomous mobile robot,” in 2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011, 2011, pp. 138–143, doi: 10.1109/ROBIO.2011.6181275.
K. Tanaka et al., “Design of operating software and electrical system of mobile robot for environmental monitoring,” in 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014, 2014, pp. 1763–1768, doi: 10.1109/ROBIO.2014.7090590.
M. Trincavelli, M. Reggente, S. Coradeschi, A. Loutfi, H. Ishida, and A. J. Lilienthal, “Towards environmental monitoring with mobile robots,” in 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 2008, pp. 2210–2215, doi: 10.1109/IROS.2008.4650755.
H. Durmus and E. O. Gunes, “Integration of the mobile robot and internet of things to collect data from the agricultural fields,” in 2019 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019, Jul. 2019, pp. 1–5, doi: 10.1109/Agro-Geoinformatics.2019.8820578.
L. Cancar, D. Sanz, J. D. Hernández, J. Del Cerro, and A. Barrientos, “Precision humidity and temperature measuring in farming using newer ground mobile robots,” in Advances in Intelligent Systems and Computing, 2014, vol. 252, pp. 443–456, doi: 10.1007/978-3-319-03413-3_32.
S. Thenmozhi, V. Mahima, and R. Maheswar, “GPS based autonomous ground vehicle for agricultural utility,” Lect. Notes Networks Syst., vol. 33, pp. 143–150, 2019, doi: 10.1007/978-981-10-8204-7_14.
A. S. Pramod and T. V. Jithinmon, “Development of mobile dual PR arm agricultural robot,” in Journal of Physics: Conference Series, Aug. 2019, vol. 1240, no. 1, pp. 1–10, doi: 10.1088/1742-6596/1240/1/012034.
C. Potena, D. Nardi, and A. Pretto, “Fast and Accurate Crop and Weed Identification with Summarized Train Sets for Precision Agriculture,” in Advances in Intelligent Systems and Computing, 2017, vol. 531, pp. 105–121, doi: 10.1007/978-3-319-48036-7_9.
S. S. Sadistap, B. A. Botre, H. Pandit, . C., and A. Rao, “Embedded mobile farm robot for identification of diseased plants,” in Fifth International Conference on Digital Image Processing (ICDIP 2013), Jul. 2013, vol. 8878, p. 88783S, doi: 10.1117/12.2031075.
S. Bhandari, A. Raheja, R. L. Green, and D. Do, “Towards collaboration between unmanned aerial and ground vehicles for precision agriculture,” in Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II, May 2017, vol. 10218, p. 1021806, doi: 10.1117/12.2262049.
B. V. Dimaya et al., “Mobile soil robot collector via smartphone with global positioning system for navigation,” in 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018, Mar. 2019, pp. 1–6, doi: 10.1109/HNICEM.2018.8666240.
A. Vasudevan, D. A. Kumar, and N. S. Bhuvaneswari, “Precision farming using unmanned aerial and ground vehicles,” in Proceedings - 2016 IEEE International Conference on Technological Innovations in ICT for Agriculture and Rural Development, TIAR 2016, Dec. 2016, pp. 146–150, doi: 10.1109/TIAR.2016.7801229.
E. Ozgul and U. Celik, “Design and implementation of semi-autonomous anti-pesticide spraying and insect repellent mobile robot for agricultural applications,” in 2018 5th International Conference on Electrical and Electronics Engineering, ICEEE 2018, Jun. 2018, pp. 233–237, doi: 10.1109/ICEEE2.2018.8391337.
X. Niu, T. Yu, J. Tang, and L. Chang, “An online solution of liDAR scan matching aided inertial navigation system for indoor mobile mapping,” vol. 2017, pp. 1–11, Jul. 2017, doi: 10.1155/2017/4802159.
Z. Shan, R. Li, and S. Schwertfeger, “RGBD-Inertial trajectory estimation and mapping for ground robots,” Sensors, vol. 19, no. 10, p. 2251, May 2019, doi: 10.3390/s19102251.
F. Yan, G. He, Y. Zhuang, and H. Chang, “Scene understanding and semantic mapping for unmanned ground vehicles using 3d point clouds,” in 8th International Conference on Information Science and Technology, ICIST 2018, Aug. 2018, pp. 335–341, doi: 10.1109/ICIST.2018.8426139.
F. Demim, A. Nemra, K. Louadj, M. Hamerlain, and A. Bazoula, “An adaptive SVSF-SLAM algorithm to improve the success and solving the UGVs cooperation problem,” J. Exp. Theor. Artif. Intell., vol. 30, no. 3, pp. 389–414, May 2018, doi: 10.1080/0952813X.2017.1409282.
M. Begum, G. K. I. Mann, and R. G. Gosine, “Integrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots,” Appl. Soft Comput., vol. 8, no. 1, pp. 150–165, Jan. 2008, doi: 10.1016/j.asoc.2006.11.010.
F. Demim, A. Nemra, K. Louadj, Z. Mehal, M. Hamerlain, and A. Bazoula, “Simultaneous localization and mapping algorithm for unmanned ground vehicle with SVSF filter,” in Proceedings of 2016 8th International Conference on Modelling, Identification and Control, ICMIC 2016, Jan. 2017, pp. 155–162, doi: 10.1109/ICMIC.2016.7804291.
B. Browning, J. E. Deschaud, D. Prasser, and P. Rander, “3D Mapping for high-fidelity unmanned ground vehicle lidar simulation,” Int. J. Rob. Res., vol. 31, no. 12, pp. 1349–1376, Oct. 2012, doi: 10.1177/0278364912460288.
M. Imperoli, C. Potena, D. Nardi, G. Grisetti, and A. Pretto, “An effective multi-cue positioning system for agricultural robotics,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3685–3692, Oct. 2018, doi: 10.1109/LRA.2018.2855052.
C. Urmson et al., “Autonomous driving in urban environments: Boss and the urban challenge,” J. F. Robot., vol. 25, no. 8, pp. 425–466, Aug. 2008, doi: 10.1002/rob.20255.
A. Buyval, I. Afanasyev, and E. Magid, “Comparative analysis of ROS-based monocular SLAM methods for indoor navigation,” Ninth Int. Conf. Mach. Vis. (ICMV 2016), vol. 10341, p. 103411K, Mar. 2017, doi: 10.1117/12.2268809.
C. Luo, M. Krishnan, M. Paulik, B. Cui, and X. Zhang, “A novel lidar-driven two-level approach for real-time unmanned ground vehicle navigation and map building,” in Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, Feb. 2014, vol. 9025, p. 902503, doi: 10.1117/12.2037963.
J. I. Rejas, A. Sanchez, G. Glez-De-Rivera, M. Prieto, and J. Garrido, “Environment mapping using a 3D laser scanner for unmanned ground vehicles,” Microprocess. Microsyst., vol. 39, no. 8, pp. 939–949, Nov. 2015, doi: 10.1016/j.micpro.2015.10.003.
J. Gregory, D. Baran, and A. W. Evans, “Evaluating the presentation and usability of 2D and 3D maps generated by unmanned ground vehicles,” in Unmanned Systems Technology XV, May 2013, vol. 8741, p. 87410G, doi: 10.1117/12.2016316.
F. Amigoni and V. Caglioti, “An information-based exploration strategy for environment mapping with mobile robots,” Rob. Auton. Syst., vol. 58, no. 5, pp. 684–699, May 2010, doi: 10.1016/j.robot.2009.11.005.
A. Howard, L. E. Parker, and G. S. Sukhatme, “Experiments with a large heterogeneous mobile robot team: Exploration, mapping, deployment and detection,” in International Journal of Robotics Research, May 2006, vol. 25, no. 5–6, pp. 431–447, doi: 10.1177/0278364906065378.
J. Rodríguez-Araújo, J. J. Rodríguez-Andina, J. Fariña, and M. Y. Chow, “Field-programmable system-on-chip for localization of UGVs in an indoor ispace,” IEEE Trans. Ind. Informatics, vol. 10, no. 2, pp. 1033–1043, May 2014, doi: 10.1109/TII.2013.2294112.
Publicado
Número
Sección
Licencia
Derechos de autor 2021 Ingeniare
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
