Hostname: page-component-7b7567c8c-kwt9d Total loading time: 0 Render date: 2026-11-14T16:53:30.854Z Has data issue: false hasContentIssue false
  • English
  • Français

A New Sensor for Robotic Mars Rovers in Sandy Terrains Predicting Critical Soil Flow Using the Spiral Soil Flow Model

Published online by Cambridge University Press:  22 June 2020

Saeed EbrahimiOpen the ORCID record for Saeed Ebrahimi[Opens in a new window],
Arman Mardani and
Khalil Alipour
Saeed Ebrahimi*
Affiliation:
Department of Mechanical Engineeng, Yazd University, Yazd, Iran
Arman Mardani
Affiliation:
Department of Mechanical Engineeng, Yazd University, Yazd, Iran
Khalil Alipour
Affiliation:
Advanced Service Robots (ASR) Lab, Department of Mechatronics Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
*
*Corresponding author. E-mail: ebrahimi@yazd.ac.ir
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

The current contribution presents a new sinkage sensor specified for an unmanned ground vehicle to find the exact sinkage zone of a wheel interacting with the soil particles. This sensor will be wrapped around the wheel, and consequently, contact analog outputs will be used in soil deposition and bulldozing effect prediction. Furthermore, the new sensor will be used for a novel soil flow calculation estimating the total mass variation of the control volume of soil particles beneath the wheel. Accordingly, the spiral model simulating the displacement of the particle is implemented to calculate the soil deposition.

Keywords

Bekker’s theoryIn-wheel sensorTraction forceUGVMars mission

Information

Type
Articles
Information
Robotica , Volume 39 , Issue 2 , February 2021, pp. 346 - 365
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

References

Walter, W. G., “An imitation of life,” Sci. Am. 182(5), 42–45 (1950).CrossRefGoogle Scholar
Tarasenko, M. V., “Transformation of the soviet space program after the cold war,” Sci. Global Secur. 4(3), 339–361 (1964).Google Scholar
Meghdari, A., Karimi, R., Pishkenari, H., Gaskarimahalle, A. and Mahboobi, S., “An effective approach for dynamic analysis of rovers,” Robotica 23(6), 771–780 (2005).CrossRefGoogle Scholar
Balaram, J., “Kinematic state estimation for a Mars rover,” Robotica 18(3), 251–262 (2000).CrossRefGoogle Scholar
Durst, P. J., Monroe, G., Bethel, C. L., Anderson, D. T. and Carruth, D. W., “A History and Overview of Mobility Modeling for Autonomous Unmanned Ground Vehicles,” Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything, Orlando, Florida, USA (2018) pp. 10643–106430.Google Scholar
Sanguino, T. D. J. M., “50 years of rovers for planetary exploration: A retrospective review for future directions,” Robot. Auto. Syst. 94, 172–185 (2017).Google Scholar
Caudill, C. M., Pontefract, A. J., Osinski, G. R., Tornabene, L. L., Pilles, E. A., Battler, M., and Hipkin, V. J., “CanMars mission Science Team operational results: Implications for operations and the sample selection process for Mars Sample Return (MSR),” Planet. Space Sci. 172, 43–56 (2019).CrossRefGoogle Scholar
Francis, R., Pilles, E., Osinski, G. R., McIsaac, K., Gaines, D. and Kissi, J., “Utility and applications of rover science autonomy capabilities: outcomes from a high-fidelity analogue mission simulation,” Planet. Space Sci. 170, 52–60 (2019).CrossRefGoogle Scholar
Robson, N. and Ghosh, S., “Geometric design of planar mechanisms based on virtual guides for manipulation,” Robotica 34(12), 2653–2668 (2016).CrossRefGoogle Scholar
Tarokh, M. and Ho, H., “Kinematics-based simulation and animation of articulated rovers traversing uneven terrains,” Robotica. 37(6), 1057–1072 (2019).CrossRefGoogle Scholar
Cardile, D., Viola, N., Chiesa, S. and Rougier, A., “Applied design methodology for lunar rover elastic wheel,” Acta Astronautica 81(1), 1–11 (2018).CrossRefGoogle Scholar
Krid, M., Benamar, F. and Zamzami, Z., “Design of an active device for controlling lateral stability of fast mobile robot,” Robotica 34(11), 2629–2651 (2016).CrossRefGoogle Scholar
Nie, C., Assaliyski, M. and Spenko, M., “Design and experimental characterization of an omnidirectional unmanned ground vehicle for unstructured terrain,” Robotica 33(9), 1984–2000 (2015).Google Scholar
Shimoda, S., Kuroda, Y. and Iagnemma, K., “High-speed navigation of unmanned ground vehicles on uneven terrain using potential fields,” Robotica. 25(4), 409–424 (2007).CrossRefGoogle Scholar
Baratta, M., Genta, G., Laurenzano, D. and Misul, D., “Exploring the surface of the Moon and Mars: What kind of ground vehicles are required?,” Acta Astronautica. 154, 204–213 (2019).CrossRefGoogle Scholar
Ebrahimi, S. and Mardani, A., “Terramechanics-Based Performance Enhancement of the Wide Robotic Wheel on the Soft Terrains, Part I: Wheel Shape Optimization,” The 4th IEEE International Conference on Robotics and Mechatronics (Amirkabir University of Technology, Tehran, Iran, 2017) pp. 260–265.Google Scholar
Mardani, A. and Ebrahimi, S., “Terramechanics-Based Performance Enhancement of the Wide Robotic Wheel on the Soft Terrains, Part II: Torque Control of the Optimized Wheel,” The 4th IEEE International Conference on Robotics and Mechatronics (Amirkabir University of Technology, Tehran, Iran, 2017) pp. 480–485.Google Scholar
Gao, H., Chen, C., Ding, L., Li, W., Yu, H., Xia, K. and Liu, Z., “Tracking control of WMRs on loose soil based on mixed H2/H8 control with longitudinal slip ratio estimation,” Acta Astronautica 140, 49–58 (2017).CrossRefGoogle Scholar
Mardani, A., Ebrahimi, S. and Alipour, K., “New adaptive segmented wheel for locomotion improvement of field robots on soft terrain,” J. Intell. Robot. Syst. 97(3), 695–717 (2019).CrossRefGoogle Scholar
Nicolini, A., Mocera, F. and Somà, A., “Multibody simulation of a tracked vehicle with deformable ground contact model,” Proc. Inst. Mech. Eng. Part K J. Multi-body Dyn. 233(1), 152–162.Google Scholar
Ebrahimi, S. and Mardani, A., “A new resistive belt sensor for multipoint contact detection of robotic wheels,” Iran. J. Sci. Tech. Trans. Mech. Eng. 43(1), 399–414.Google Scholar
Mardani, A. and Ebrahimi, S., “Simultaneous surface scanning and stability analysis of wheeled mobile robots using a new spatial sensitive shield sensor,” Robot. Auto. Syst. 98, 1–14 (2017).CrossRefGoogle Scholar
Nagatani, K., Ikeda, A., Sato, K. and Yoshida, K., “Accurate Estimation of Drawbar Pull of Wheeled Mobile Robots Traversing Sandy Terrain Using Built-in Force Sensor Array Wheel,” Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA (2009) pp. 2373–2378.Google Scholar
Halatci, I., Brooks, C. and Iagnemma, K., “A study of visual and tactile terrain classification and classifier fusion for planetary exploration rovers,” Robotica 26(6), 767–779 (2008).CrossRefGoogle Scholar
Guo, J., Ding, L., Gao, H., Liu, G. and Peng, H., “An apparatus to measure wheel–soil interactions on sandy terrains,” IEEE/ASME Trans. Mechatron. 23(1), 352–363 (2018).CrossRefGoogle Scholar
Spiteri, C., Al-Milli, S., Gao, Y. and de León, A. S., “Real-time visual sinkage detection for planetary rovers,” Robot. Auto. Syst. 72, 307–317 (2015).CrossRefGoogle Scholar
Bernstein, R., “Probleme zur experimentellen Motorpflugmechanik,” Der Motorwagen. 16(6), 199–206 (1913).Google Scholar
Jia, Z., Smith, W. and Peng, H., “Fast analytical models of wheeled locomotion in deformable terrain for mobile robots,” Robotica 31(1), 35–53 (2013).CrossRefGoogle Scholar
Gao, H., Ly, F., Yuan, B. and Deng, Z., “Sinkage definition and visual detection for planetary rovers wheels on rough terrain based on wheel–soil interaction boundary,” Robot. Auto. Syst. 98, 222–240 (2017).CrossRefGoogle Scholar
Jia, Z., Smith, W. and Peng, H., “Terramechanics-based wheel–terrain interaction model and its applications to off-road wheeled mobile robots,” Robotica 30(3), 491–503 (2012).CrossRefGoogle Scholar
Hutangkabodee, S., Zweiri, Y. H., Seneviratne, L. D. and Althoefer, K., “Soil parameter identification for wheel-terrain interaction dynamics and traversability prediction,” Int. J. Autom. Comput. 3(3), 244–251 (2006).CrossRefGoogle Scholar
Kumar, P. G. and Jayalekshmi, S., “A Study on Wheel Sinkage and Rolling Resistance with Variations in Wheel Geometry for Plain and Lugged Wheels on TRI-1 Soil Simulant,” IOP Conference Series: Materials Science and Engineering, vol. 330-1 (IOP, Tamil Nadu, India, 2018).Google Scholar
Zachmann, G., Virtual Reality in Assembly Simulation-Collision Detection, Simulation Algorithms, and Interaction Techniques, Chapter 3 (Doctoral Dissertation, Department of Computer Science, the Technical University of Darmstadt, Germany, 2000).Google Scholar
Wong, J. Y., Terramechanics and Off-Road Vehicle Engineering: Terrain Behaviour, Off-Road Vehicle Performance and Design, Chapter 4 (Elsevier, Butterworth-Heinemann, UK, 2009) pp. 86.CrossRefGoogle Scholar
Ding, L., Yang, H., Gao, H., Li, N., Deng, Z., Guo, J. and Li, N., “Terramechanics-based modeling of sinkage and moment for in-situ steering wheels of mobile robots on deformable terrain,” Mech. Mach. Theory 116, 14–33 (2017).CrossRefGoogle Scholar
Tran, T. H., Kwok, N. M., Scheding, S. and Ha, Q. p., “Dynamic Modelling of Wheel-Terrain Interaction of a UGV,” IEEE International conference on automation Science and Engineering CASE, AZ, USA (2007) pp. 369–374.Google Scholar
Du, Y., Gao, J., Jiang, L. and Zhang, Y. “Development and numerical validation of an improved prediction model for wheel-soil interaction under multiple operating conditions,” J. Terramech. 79, 1–21 (2018).CrossRefGoogle Scholar
Jiang, M., Dai, Y., Cui, L. and Xi, B., “Experimental and DEM analyses on wheel-soil interaction,” J. Terramech. 76, 15–28 (2018).CrossRefGoogle Scholar
Jiang, M., Liu, F., Shen, Z. and Zheng, M., “Distinct element simulation of lugged wheel performance under extraterrestrial environmental effects,” Acta Astronautica. 99, 37–51 (2014).CrossRefGoogle Scholar
Wong, J. Y., “Behavior of soil beneath rigid wheels,” J. Agric. Eng. Res. 12(4), 257–269 (1967).CrossRefGoogle Scholar
Fukami, K., Ueno, M., Hashiguchi, K. and Okayasu, T., “Mathematical models for soil displacement under a rigid wheel,” J. Terramech. 43(3), 287–301 (2006).Google Scholar
Tijink, F. G. J., Load-Bearing Processes in Agricultural Wheel-Soil Systems (Doctoral Dissertation, Soil Technology Group, Agricultural University, Wageningen University, Netherlands, 1988) pp. 77–78.Google Scholar
Azimi, A., Wheel-Soil Interaction Modelling for Rover Simulation and Analysis (Doctoral Dissertation, McGill University, 2014).Google Scholar
Zhou, F., Arvidson, R. E., Bennett, K., Trease, B., Lindemann, R., Bellutta, P. and Senatore, C., “Simulations of Mars rover traverses,” J. Field Robot. 31(1), 141–160 (2104).CrossRefGoogle Scholar
Arvidson, R. E., Iagnemma, K. D., Maimone, M., Fraeman, A. A., Zhou, F., Heverly, M. C. and Vasavada, A. R., “Mars science laboratory curiosity rover megaripple crossings up to sol 710 in gale crater,” J. Field Robot. 34(3), 495–518 (2017).CrossRefGoogle Scholar
https://nasa3d.arc.nasa.gov/detail/curiosity-pathGoogle Scholar
Iagnemma, K., Senator, C., Trease, B., Arvidson, R., Bennett, K., Shaw, A. and Lindemann, R., “Terramechanics Modeling of Mars Surface Exploration Rovers for Simulation and Parameter Estimation,” ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers (2011) pp. 805–812.Google Scholar
Zhang, Z. Z., Lv, J. G., Song, B., Guo, S. Y. and Gao, F., “Development of non-pneumatic tire technology,” Appl. Mech. Mater. 427, 191–194 (2013).Google Scholar
Feng, Y. T. and Owen, D. R. J., “Discrete element modelling of large scale particle systems I: Exact scaling laws,” Comput. Part. Mech. 1(2), 159–168 (2014).Google Scholar
https://physics.stackexchange.com/questions/12806/roughly-how-many-atoms-thick-is-the-layer-of-graph-ite-left-by-a-pencil-writing-oGoogle Scholar