Measurement of a Vibration on a Robotic Vehicle
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
UJEP-IGA-JR-2021-48-003-2
The Internal Grant Agency of Jan Evangelista Purkyne University in Usti nad Labem, Czech Republic
PubMed
36433244
PubMed Central
PMC9695174
DOI
10.3390/s22228649
PII: s22228649
Knihovny.cz E-zdroje
- Klíčová slova
- accumulators, electric motors, robotic vehicle, steering, vibration,
- Publikační typ
- časopisecké články MeSH
This article deals with the design and construction of a robotic vehicle. The first part of the paper focuses on the selection of suitable variants for the robotic vehicle arrangement, i.e., frame, electric motors with gearboxes, wheels, steering and accumulators. Based on the selection of individual components, the robotic vehicle was built. An important part of the robotic vehicle was the design of the suspension of the front wheels. The resulting shape of the springs was experimentally developed from several design variants and subsequently produced by an additive manufacturing process. The last part of article is devoted to the experimental measurement of the acceleration transfer to the upper part of the frame during the passage of the robotic vehicle over differently arranged obstacles. Experimental measurements measured the accelerations that are transferred to the top of the robotic vehicle frame when the front wheels of the vehicle cross over the obstacle (obstacles). The maximum acceleration values are 0.0588 m/s2 in the x-axis, 0.0149 m/s2 in the y-axis and 0.5755 m/s2 in the z-axis. This experimental solution verifies the stiffness of the designed frame and the damping effect of the selected material of the designed springs on the front wheels of the robotic vehicle.
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Martínez-Gutiérrez A., Díez-González J., Ferrero-Guillén R., Verde P., Álvarez R., Perez H. Digital Twin for Automatic Transportation in Industry 4.0. Sensors. 2021;21:3344. doi: 10.3390/s21103344. PubMed DOI PMC
Santos J., Rebelo P.M., Rocha L.F., Costa P., Veiga G. A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario. Robotics. 2021;10:72. doi: 10.3390/robotics10020072. DOI
Kala R., Warwick K. Motion Planning of Autonomous Vehicles in a Non-Autonomous Vehicle Environment without Speed Lanes. Eng. Appl. Artif. Intell. 2013;26:1588–1601. doi: 10.1016/j.engappai.2013.02.001. DOI
Keviczky T., Balas G. Software-Enabled Receding Horizon Control for Autonomous Unmanned Aerial Vehicle Guidance. J. Guid. Control Dyn. 2006;29:680–694. doi: 10.2514/1.15562. DOI
Olmi R., Secchi C., Fantuzzi C. Coordinating the Motion of Multiple AGVs in Automatic Warehouses; Proceedings of the Workshop on Robotics and Intelligent Transportation Systems; Anchorage, AK, USA. 8 May 2010.
Almasri M., Elleithy K., Alajlan A. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation. Sensors. 2016;16:24. doi: 10.3390/s16010024. PubMed DOI PMC
Anandaraman C., Vikram A., Sankar M., Natarajan R. Evolutionary approaches for scheduling a flexible manufacturing system with automated guided vehicles and robots. Int. J. Ind. Eng. Comput. 2012;3:627–648. doi: 10.5267/j.ijiec.2012.03.004. DOI
Confessore G., Fabiano M., Liotta G. A network flow based heuristic approach for optimising AGV movements. J. Intell. Manuf. 2013;24:405–419. doi: 10.1007/s10845-011-0612-7. DOI
De Ryck M., Versteyhe M., Shariatmadar K. Resourcemanagement in decentralized industrial automated guided vehicle systems. J. Manuf. Syst. 2020;54:204–214. doi: 10.1016/j.jmsy.2019.11.003. DOI
Lasi H., Fettke P.D.P., Kemper H.-G., Feld D.-I.T., Hoffmann D.-H.M. Industry 4.0. Bus. Inf. Syst. Eng. 2014;6:239–242. doi: 10.1007/s12599-014-0334-4. DOI
Golan M., Cohen Y., Singer G. A framework for operator—Workstation interaction in Industry 4.0. Int. J. Prod. Res. 2019;58:2421–2432. doi: 10.1080/00207543.2019.1639842. DOI
Citroni R., Di Paolo F., Livreri P. A Novel Energy Harvester for Powering Small UAVs: Performance Analysis, Model Validation and Flight Results. Sensors. 2019;19:1771. doi: 10.3390/s19081771. PubMed DOI PMC
Tsugawa S. Automated driving systems: Common ground of automobiles and robots. Int. J. Hum. Robot. 2011;8:1–12. doi: 10.1142/S0219843611002319. DOI
Vlk F. Dynamika Motorových Vozidel: Jízdní Odpory, Hnací Charakteristika, Brzdění, Odpružení, Řiditelnost, Ovladatelnost, Stabilita. 1st ed. Vlk František; Brno, Czech Republic: 2000. p. 434.
Ikeda H., Atoji S., Amemiya M., Tajima S., Kitada T., Fukai K., Sato K. Recovery Strategy for Overturned Wheeled Vehicle Using a Mobile Robot and Experimental Validation. Sensors. 2022;22:5952. doi: 10.3390/s22165952. PubMed DOI PMC
Visconte C., Cavallone P., Carbonari L., Botta A., Quaglia G. Design of a Mechanism with Embedded Suspension to Reconfigure the Agri_q Locomotion Layout. Robotics. 2021;10:15. doi: 10.3390/robotics10010015. DOI
Zhang X., Yuan S., Yin X., Li X., Qu X., Liu Q. Estimation of Skid-Steered Wheeled Vehicle States Using STUKF with Adaptive Noise Adjustment. Appl. Sci. 2021;11:10391. doi: 10.3390/app112110391. DOI
Zhao J., Han T., Wang S., Liu C., Fang J., Liu S. Design and Research of All-Terrain Wheel-Legged Robot. Sensors. 2021;21:5367. doi: 10.3390/s21165367. PubMed DOI PMC
Svoboda M., Chalupa M., Jelen K., Lopot F., Kubový P., Sapieta M., Krobot Z., Suszyński M. Load Measurement of the Cervical Vertebra C7 and the Head of Passengers of a Car While Driving across Uneven Terrain. Sensors. 2021;21:3849. doi: 10.3390/s21113849. PubMed DOI PMC
Klimenda F., Skocilas J., Skocilasova B., Soukup J., Cizek R. Vertical Oscillation of Railway Vehicle Chassis with Asymmetry Effect Consideration. Sensors. 2022;22:4033. doi: 10.3390/s22114033. PubMed DOI PMC
Erol R., Sahin C., Baykasoglu A., Kaplanoglu V. A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems. Appl. Soft Comput. J. 2012;12:1720–1732. doi: 10.1016/j.asoc.2012.02.001. DOI
Pacejka H.B. Proceedings of the IUTAM Sympozium. Pelft; Prague, Czech Republic: 1975. The Dynamics of Vehicles on Roads and on Railway Tracks.
Abuabiah M., Dabbas Y., Herzallah L., Alsurakji I.H., Assad M., Plapper P. Analytical Study on the Low-Frequency Vibrations Isolation System for Vehicle’s Seats Using Quasi-Zero-Stiffness Isolator. Appl. Sci. 2022;12:2418. doi: 10.3390/app12052418. DOI
[(accessed on 5 June 2022)]. Available online: https://www.materialpro3d.cz/cpe-filamenty/cpe-hg100-caramel-brown-1-75mm-750g-fillamentum/
Vachalek J., Toth F., Krasnansky P., Capucha L. Design and Construction of a Robotic Vehicle with Omni-Directional Mecanum Wheels. Trans. VŠB Tech. Univ. Ostrav. Mech. Ser. 2014;1:97–104. doi: 10.22223/tr.2014-1/1983. DOI
Papoutsidakis M., Kalovrektis K., Drosos C., Stamoulis G. Design of an Autonomous Robotic Vehicle for Area Mapping and Remote Monitoring. Int. J. Comput. Appl. 2017;167:36–41. doi: 10.5120/ijca2017914496. DOI
Song J.-B., Kim J.-K. Energy Efficient Drive of an Omnidirectional Mobile Robot with Steerable Omnidirectional Wheels; Proceedings of the 16th Triennial World Congress; Prague, Czech Republic. 3–8 July 2005; pp. 73–78.
Singh S., Burks T.B., Lee W.S. Autonomous Robotic Vehicle Development for Greenhouse Spraying. Am. Soc. Agric. Biol. Eng. 2002;48:2355–2361. doi: 10.13031/2013.20074. DOI
Vibration Measurements on a Six-Axis Collaborative Robotic Arm-Part I