- -

A review of mobile robots: Concepts, methods, theoretical framework, and applications

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Show simple item record

Files in this item

dc.contributor.author Rubio Montoya, Francisco José es_ES
dc.contributor.author Valero Chuliá, Francisco José es_ES
dc.contributor.author Llopis Albert, Carlos es_ES
dc.date.accessioned 2020-12-19T04:31:41Z
dc.date.available 2020-12-19T04:31:41Z
dc.date.issued 2019-04-16 es_ES
dc.identifier.issn 1729-8806 es_ES
dc.identifier.uri http://hdl.handle.net/10251/157496
dc.description.abstract [EN] Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great examples of mobile robots. They can be distinguished from other robots by their ability to move autonomously, with enough intelligence to react and make decisions based on the perception they receive from the environment. Mobile robots must have some source of input data, some way of decoding that input, and a way of taking actions (including its own motion) to respond to a changing world. The need to sense and adapt to an unknown environment requires a powerful cognition system. Nowadays, there are mobile robots that can walk, run, jump, and so on like their biological counterparts. Several fields of robotics have arisen, such as wheeled mobile robots, legged robots, flying robots, robot vision, artificial intelligence, and so on, which involve different technological areas such as mechanics, electronics, and computer science. In this article, the world of mobile robots is explored including the new trends. These new trends are led by artificial intelligence, autonomous driving, network communication, cooperative work, nanorobotics, friendly human-robot interfaces, safe human-robot interaction, and emotion expression and perception. Furthermore, these news trends are applied to different fields such as medicine, health care, sports, ergonomics, industry, distribution of goods, and service robotics. These tendencies will keep going their evolution in the coming years. es_ES
dc.description.sponsorship The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Spanish Ministry of Economy and Competitiveness, which has funded the DPI2013-44227-R project. es_ES
dc.language Inglés es_ES
dc.publisher SAGE Publications es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//DPI2013-44227-R/ES/METODOLOGIA DE DISEÑO DE SISTEMAS BIOMECATRONICOS. APLICACION AL DESARROLLO DE UN ROBOT PARALELO HIBRIDO PARA DIAGNOSTICO Y REHABILITACION/ es_ES
dc.relation.ispartof International Journal of Advanced Robotic Systems es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Cognition es_ES
dc.subject Locomotion es_ES
dc.subject Motion planning es_ES
dc.subject Mobile robotics es_ES
dc.subject Navigation es_ES
dc.subject Perception es_ES
dc.subject Sensoring es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title A review of mobile robots: Concepts, methods, theoretical framework, and applications es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1177/1729881419839596 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials es_ES
dc.description.bibliographicCitation Rubio Montoya, FJ.; Valero Chuliá, FJ.; Llopis Albert, C. (2019). A review of mobile robots: Concepts, methods, theoretical framework, and applications. International Journal of Advanced Robotic Systems. 16(2):1-22. https://doi.org/10.1177/1729881419839596 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1177/1729881419839596 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 22 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\395295 es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.description.references Brunete, A., Ranganath, A., Segovia, S., de Frutos, J. P., Hernando, M., & Gambao, E. (2017). Current trends in reconfigurable modular robots design. International Journal of Advanced Robotic Systems, 14(3), 172988141771045. doi:10.1177/1729881417710457 es_ES
dc.description.references Bajracharya, M., Maimone, M. W., & Helmick, D. (2008). Autonomy for Mars Rovers: Past, Present, and Future. Computer, 41(12), 44-50. doi:10.1109/mc.2008.479 es_ES
dc.description.references Carsten, J., Rankin, A., Ferguson, D., & Stentz, A. (2007). Global Path Planning on Board the Mars Exploration Rovers. 2007 IEEE Aerospace Conference. doi:10.1109/aero.2007.352683 es_ES
dc.description.references Grotzinger, J. P., Crisp, J., Vasavada, A. R., Anderson, R. C., Baker, C. J., Barry, R., … Wiens, R. C. (2012). Mars Science Laboratory Mission and Science Investigation. Space Science Reviews, 170(1-4), 5-56. doi:10.1007/s11214-012-9892-2 es_ES
dc.description.references Khatib, O., Yeh, X., Brantner, G., Soe, B., Kim, B., Ganguly, S., … Creuze, V. (2016). Ocean One: A Robotic Avatar for Oceanic Discovery. IEEE Robotics & Automation Magazine, 23(4), 20-29. doi:10.1109/mra.2016.2613281 es_ES
dc.description.references Ceccarelli, M. (2012). Notes for a History of Grasping Devices. Mechanisms and Machine Science, 3-16. doi:10.1007/978-1-4471-4664-3_1 es_ES
dc.description.references Campion, G., & Chung, W. (2008). Wheeled Robots. Springer Handbook of Robotics, 391-410. doi:10.1007/978-3-540-30301-5_18 es_ES
dc.description.references Ferriere, L., Raucent, B., & Campion, G. (s. f.). Design of omnimobile robot wheels. Proceedings of IEEE International Conference on Robotics and Automation. doi:10.1109/robot.1996.509271 es_ES
dc.description.references Campion, G., Bastin, G., & Dandrea-Novel, B. (1996). Structural properties and classification of kinematic and dynamic models of wheeled mobile robots. IEEE Transactions on Robotics and Automation, 12(1), 47-62. doi:10.1109/70.481750 es_ES
dc.description.references Bałchanowski, J. (2012). Mobile Wheel-Legged Robot: Researching of Suspension Leveling System. Mechanisms and Machine Science, 3-12. doi:10.1007/978-94-007-5125-5_1 es_ES
dc.description.references Williams, R. L., Carter, B. E., Gallina, P., & Rosati, G. (2002). Dynamic model with slip for wheeled omnidirectional robots. IEEE Transactions on Robotics and Automation, 18(3), 285-293. doi:10.1109/tra.2002.1019459 es_ES
dc.description.references Chan, R. P. M., Stol, K. A., & Halkyard, C. R. (2013). Review of modelling and control of two-wheeled robots. Annual Reviews in Control, 37(1), 89-103. doi:10.1016/j.arcontrol.2013.03.004 es_ES
dc.description.references Kim, H., & Kim, B. K. (2014). Online Minimum-Energy Trajectory Planning and Control on a Straight-Line Path for Three-Wheeled Omnidirectional Mobile Robots. IEEE Transactions on Industrial Electronics, 61(9), 4771-4779. doi:10.1109/tie.2013.2293706 es_ES
dc.description.references Carbone, G., & Ceccarelli, M. (2005). Legged Robotic Systems. Cutting Edge Robotics. doi:10.5772/4669 es_ES
dc.description.references Chestnutt, J., Lau, M., Cheung, G., Kuffner, J., Hodgins, J., & Kanade, T. (s. f.). Footstep Planning for the Honda ASIMO Humanoid. Proceedings of the 2005 IEEE International Conference on Robotics and Automation. doi:10.1109/robot.2005.1570188 es_ES
dc.description.references Arikawa, K., & Hirose, S. (s. f.). Development of quadruped walking robot TITAN-VIII. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS ’96. doi:10.1109/iros.1996.570670 es_ES
dc.description.references Kurazume, R., Byong-won, A., Ohta, K., & Hasegawa, T. (s. f.). Experimental study on energy efficiency for quadruped walking vehicles. Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453). doi:10.1109/iros.2003.1250697 es_ES
dc.description.references Hirose, S., Fukuda, Y., Yoneda, K., Nagakubo, A., Tsukagoshi, H., Arikawa, K., … Hodoshima, R. (2009). Quadruped walking robots at Tokyo Institute of Technology. IEEE Robotics & Automation Magazine, 16(2), 104-114. doi:10.1109/mra.2009.932524 es_ES
dc.description.references Stoica, A., Carbone, G., Ceccarelli, M., & Pisla, D. (2010). Cassino Hexapod : Experiences and new leg design. 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR). doi:10.1109/aqtr.2010.5520756 es_ES
dc.description.references Bares, J. E., & Wettergreen, D. S. (1999). Dante II: Technical Description, Results, and Lessons Learned. The International Journal of Robotics Research, 18(7), 621-649. doi:10.1177/02783649922066475 es_ES
dc.description.references Schiele, A., Romstedt, J., Lee, C., Henkel, H., Klinkner, S., Bertrand, R., … Michaelis, H. (2008). NanoKhod Exploration Rover - A Rugged Rover Suited for Small, Low-Cost, Planetary Lander Mission. IEEE Robotics & Automation Magazine, 15(2), 96-107. doi:10.1109/mra.2008.917888 es_ES
dc.description.references Takayama, T., & Hirose, S. (2003). Development of Souryu I & II -Connected Crawler Vehicle for Inspection of Narrow and Winding Space. Journal of Robotics and Mechatronics, 15(1), 61-69. doi:10.20965/jrm.2003.p0061 es_ES
dc.description.references Cuesta, F., & Ollero, A. (2005). Intelligent Mobile Robot Navigation. Springer Tracts in Advanced Robotics. doi:10.1007/b14079 es_ES
dc.description.references Ohya, I., Kosaka, A., & Kak, A. (1998). Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing. IEEE Transactions on Robotics and Automation, 14(6), 969-978. doi:10.1109/70.736780 es_ES
dc.description.references Desouza, G. N., & Kak, A. C. (2002). Vision for mobile robot navigation: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(2), 237-267. doi:10.1109/34.982903 es_ES
dc.description.references Borenstein, J., Everett, H. R., Feng, L., & Wehe, D. (1997). Mobile robot positioning: Sensors and techniques. Journal of Robotic Systems, 14(4), 231-249. doi:10.1002/(sici)1097-4563(199704)14:4<231::aid-rob2>3.0.co;2-r es_ES
dc.description.references Betke, M., & Gurvits, L. (1997). Mobile robot localization using landmarks. IEEE Transactions on Robotics and Automation, 13(2), 251-263. doi:10.1109/70.563647 es_ES
dc.description.references Kuffner, J., Nishiwaki, K., Kagami, S., Inaba, M., & Inoue, H. (2005). Motion Planning for Humanoid Robots. Robotics Research. The Eleventh International Symposium, 365-374. doi:10.1007/11008941_39 es_ES
dc.description.references Lee, Y.-J., & Bien, Z. (2002). Path planning for a quadruped robot: an artificial field approach. Advanced Robotics, 16(7), 609-627. doi:10.1163/15685530260390746 es_ES
dc.description.references Petres, C., Pailhas, Y., Patron, P., Petillot, Y., Evans, J., & Lane, D. (2007). Path Planning for Autonomous Underwater Vehicles. IEEE Transactions on Robotics, 23(2), 331-341. doi:10.1109/tro.2007.895057 es_ES
dc.description.references P. Raja. (2012). Optimal path planning of mobile robots: A review. International Journal of the Physical Sciences, 7(9). doi:10.5897/ijps11.1745 es_ES
dc.description.references Hart, P., Nilsson, N., & Raphael, B. (1968). A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics, 4(2), 100-107. doi:10.1109/tssc.1968.300136 es_ES
dc.description.references Lozano-Pérez, T., & Wesley, M. A. (1979). An algorithm for planning collision-free paths among polyhedral obstacles. Communications of the ACM, 22(10), 560-570. doi:10.1145/359156.359164 es_ES
dc.description.references Lozano-Perez. (1983). Spatial Planning: A Configuration Space Approach. IEEE Transactions on Computers, C-32(2), 108-120. doi:10.1109/tc.1983.1676196 es_ES
dc.description.references Brooks, R. A. (1983). Solving the find-path problem by good representation of free space. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13(2), 190-197. doi:10.1109/tsmc.1983.6313112 es_ES
dc.description.references Schwartz, J. T., & Sharir, M. (1983). On the «piano movers» problem. II. General techniques for computing topological properties of real algebraic manifolds. Advances in Applied Mathematics, 4(3), 298-351. doi:10.1016/0196-8858(83)90014-3 es_ES
dc.description.references Kavraki LE. Random networks in configurations space for fast path planning. Doctoral dissertation, Department of Computer Science, Stanford University, Stanford, CA, 1994. es_ES
dc.description.references Kavraki, L. E., Latombe, J.-C., Motwani, R., & Raghavan, P. (1998). Randomized Query Processing in Robot Path Planning. Journal of Computer and System Sciences, 57(1), 50-60. doi:10.1006/jcss.1998.1578 es_ES
dc.description.references Hsu, D., Kindel, R., Latombe, J.-C., & Rock, S. (2002). Randomized Kinodynamic Motion Planning with Moving Obstacles. The International Journal of Robotics Research, 21(3), 233-255. doi:10.1177/027836402320556421 es_ES
dc.description.references Kavraki, L. E., Svestka, P., Latombe, J.-C., & Overmars, M. H. (1996). Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4), 566-580. doi:10.1109/70.508439 es_ES
dc.description.references Rubio, F., Valero, F., Sunyer, J., & Mata, V. (2009). Direct step‐by‐step method for industrial robot path planning. Industrial Robot: An International Journal, 36(6), 594-607. doi:10.1108/01439910910994669 es_ES
dc.description.references Howard, T. M., & Kelly, A. (2007). Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots. The International Journal of Robotics Research, 26(2), 141-166. doi:10.1177/0278364906075328 es_ES
dc.description.references Valero FJ. Planificación de trayectorias libres de obstáculos para un manipulador plano. Doctoral Thesis, UPV, Spain, 1990. es_ES
dc.description.references Valero, F., Mata, V., Cuadrado, J. I., & Ceccarelli, M. (1996). A formulation for path planning of manipulators in complex environments by using adjacent configurations. Advanced Robotics, 11(1), 33-56. doi:10.1163/156855397x00038 es_ES
dc.description.references Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. doi:10.1109/4235.996017 es_ES
dc.description.references Garcia, M. A. P., Montiel, O., Castillo, O., Sepúlveda, R., & Melin, P. (2009). Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation. Applied Soft Computing, 9(3), 1102-1110. doi:10.1016/j.asoc.2009.02.014 es_ES
dc.description.references Miao, H., & Tian, Y.-C. (2013). Dynamic robot path planning using an enhanced simulated annealing approach. Applied Mathematics and Computation, 222, 420-437. doi:10.1016/j.amc.2013.07.022 es_ES
dc.description.references Bobrow, J. E., Dubowsky, S., & Gibson, J. S. (1985). Time-Optimal Control of Robotic Manipulators Along Specified Paths. The International Journal of Robotics Research, 4(3), 3-17. doi:10.1177/027836498500400301 es_ES
dc.description.references Kang Shin, & McKay, N. (1985). Minimum-time control of robotic manipulators with geometric path constraints. IEEE Transactions on Automatic Control, 30(6), 531-541. doi:10.1109/tac.1985.1104009 es_ES
dc.description.references Kyriakopoulos, K. J., & Saridis, G. N. (s. f.). Minimum jerk path generation. Proceedings. 1988 IEEE International Conference on Robotics and Automation. doi:10.1109/robot.1988.12075 es_ES
dc.description.references Constantinescu, D., & Croft, E. A. (2000). Smooth and time-optimal trajectory planning for industrial manipulators along specified paths. Journal of Robotic Systems, 17(5), 233-249. doi:10.1002/(sici)1097-4563(200005)17:5<233::aid-rob1>3.0.co;2-y es_ES
dc.description.references Gasparetto, A., & Zanotto, V. (2010). Optimal trajectory planning for industrial robots. Advances in Engineering Software, 41(4), 548-556. doi:10.1016/j.advengsoft.2009.11.001 es_ES
dc.description.references JIANGdagger, Z.-P., & NIJMEIJER, H. (1997). Tracking Control of Mobile Robots: A Case Study in Backstepping**This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Alberto Isidori under the direction of Editor Tamer Başar. Automatica, 33(7), 1393-1399. doi:10.1016/s0005-1098(97)00055-1 es_ES
dc.description.references Klosowski, J. T., Held, M., Mitchell, J. S. B., Sowizral, H., & Zikan, K. (1998). Efficient collision detection using bounding volume hierarchies of k-DOPs. IEEE Transactions on Visualization and Computer Graphics, 4(1), 21-36. doi:10.1109/2945.675649 es_ES
dc.description.references Mirtich B. V-Clip: fast and robust polyhedral collision detection. Technical Report TR97-05, Mitsubishi Electric Research Laboratory, 1997. es_ES
dc.description.references Mohamed, E. F., El-Metwally, K., & Hanafy, A. R. (2011). An improved Tangent Bug method integrated with artificial potential field for multi-robot path planning. 2011 International Symposium on Innovations in Intelligent Systems and Applications. doi:10.1109/inista.2011.5946136 es_ES
dc.description.references Seder, M., & Petrovic, I. (2007). Dynamic window based approach to mobile robot motion control in the presence of moving obstacles. Proceedings 2007 IEEE International Conference on Robotics and Automation. doi:10.1109/robot.2007.363613 es_ES
dc.description.references Simmons, R. (s. f.). The curvature-velocity method for local obstacle avoidance. Proceedings of IEEE International Conference on Robotics and Automation. doi:10.1109/robot.1996.511023 es_ES


This item appears in the following Collection(s)

Show simple item record