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Prediction and Experimental Validation of Power Consumption of Skid-Steer Mobile Robots in Manufacturing Environments

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Abstract

Skid-Steer Mobile Robots (SSMRs) provide a robust and simple mechanical drive platform making them useful in many applications. Power consumption is an important consideration in the design of any mobile robot and particularly important for SSMRs because of the slipping and corresponding friction that induce large loads on the drive system. The slipping behavior is generally characterized through Instantaneous Centers of Rotation (ICR) of the contact patches and it has been established that these are functions of the system dynamics. However, the existing SSMR power models generally treat these constraints at the kinematic level by assuming constant slip rates taken from empirical data. This paper demonstrates a method to evaluate SSMR power consumption based on slip parameters that are calculated as differential equations extracted from the equations of motion. The dynamic power model is validated and then implemented on two practical manufacturing applications in which a mobile robot is climbing on steel surfaces with primary power consumption due to turning and overcoming gravity. The applications show that the dynamic ICR model plays a significant role in estimating power requirements. The results further demonstrate that the power and energy requirements for a given task depend on the payload and motion along the task in a non-linear fashion, for example showing that the minimum payload does not necessarily correspond to the minimum energy use. This outcome suggests that dynamic effects can be used to find optimal trajectories to minimize power or energy requirements.

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References

  1. Martinez, J., Mandow, A., Morales, J., Pedraza, S., Garcia-Cerezo, A.: Approximating kinematics for tracked mobile robots. Int. J. Robot. Res. 12(3), 867–878 (2005)

    Article  Google Scholar 

  2. Wang, Z., Gu, H.: A review of locomotion mechanisms of urban search and rescue robot. Indust. Robot: Intern. J. 34(4), 400–411 (2007)

    Article  Google Scholar 

  3. Canfield, S., Beard, J.: Robotic inspection in power plants. In: ISA 51st Annual Instrumentation Symposium. Knoxville (2005)

  4. Kar, M.: Prediction of track forces in skid-steering of military tracked vehicles. J. Terramech. 24(1), 75–84 (1987)

    Article  Google Scholar 

  5. Kozlowski, K., Pazderski, D.: Modeling and control of a 4-wheel skid-steering mobile robot. Int. J. Appl. Math. Comput. Sci. 14(4), 477–496 (2004)

    MathSciNet  MATH  Google Scholar 

  6. Shiller, Z., Serate, W., Hua, M.: Trajectory planning of tracked vehicles. In: IEEE International Conference on Robotics and Automation. Atlanta (1993)

  7. Mandow, A., Martinez, J., Morales, J., Blanco, J., Garcia-Cerezo, A., Gonzalez, J.: Experimental kinematics for wheeled skid-steer mobile robots. In: IEEE International Conference on Intelligent Robots and Systems. San Diego (2007)

  8. Yu, W., Chuy, O., Collins, E., Hollis, P.: Analysis and experimental verification for dynamic modeling of a skid steer wheeled vehicle. IEEE Trans. Robot. 26(2), 340–353 (2010)

    Article  Google Scholar 

  9. Kim, C., Kim, B.: Minimum-energy motion planning for differential-driven wheeled mobile robots. In: Mobile Robots Motion Planning, New Challenges, pp 193–226. InTech (2008)

  10. Sun, Z., Reif, J.: On finding energy-minimizing paths on terrains. IEEE Trans. Robot. 21(1), 102–114 (2005)

    Article  Google Scholar 

  11. Mei, Y., Lu, Y., Lee, C., Hu, Y.: Energy-efficient mobile robot exploration. In: IEEE International Conference on Robotics and Automation. Orlando (2006)

  12. Ooi, C., Schidelhauer, C.: Minimal energy path planning for wireless robots. Mobile Netw. Appl. 14(3), 309–321 (2009)

    Article  Google Scholar 

  13. Plonski, P., Tokekar, P., Isler, V.: Energy-efficient path planning for solar-powered mobile. J. Field Robotics 30(4), 583–601 (2013)

    Article  Google Scholar 

  14. Ondruska, P., Gurau, C., Marchegiani, L., Tong, C., Posner, I.: Scheduled perception for energy-efficient path following. In: IEEE International Conference on Robotics and Automation. Seattle (2015)

  15. Morales, J., Martinez, J., Mandow, A., Garcia-Cerezo, A., Pedraza, S.: Power consumption modeling of skid-steer tracked mobile robots on rigid terrain. IEEE Trans. Robot. 25(4), 1098–1108 (2009)

    Article  Google Scholar 

  16. Morales, J., Martinez, J., Mandow, A., Garcia-Cerezo, A., Gomez-Gabriel, J., Pedraza, S.: Power analysis for a skid-steered tracked mobile robot. In: IEEE International Conference on Mechatronics. New Orleans (2006)

  17. Morales, J., Martinez, J., Mandow, A., Pequeno-Boter, A., Garcia-Cerezo, A.: Simplified power consumption modeling and identification for wheeled skid-steer robotic vehicles on hard horizontal ground. In: IEEE/RSJ International Conference on Intelligent Robots and Systems. Budapest, Hungary (2010)

  18. Pentzer, J., Brennan, S., Reichard, K.: Model-based prediction of skid-steer robot kinematics using online estimation of track instantaneous centers of rotation. J. Field Robotics 31(3), 455–476 (2014)

    Article  Google Scholar 

  19. Chuy, O., Collins, E., Yu, W., Ordonez, C.: Power modeling of a skid steered wheeled robotic ground vehicle. In: IEEE Internation Conference on Robotics and Automation. Kobe (2009)

  20. Gupta, N., Ordonez, C., Collins, E.: Dynamically feasible, energy efficient motion planning for skid-steered vehicles. Auton. Robot. 41(2), 453–471 (2017)

    Article  Google Scholar 

  21. Yu, W., Collins, E., Chuy, O.: Dynamic modeling and power modeling of robotic skid-steered wheeled vehicles. In: Mobile Robots - Current Trends, pp 291–318. InTech (2011)

  22. Canfield, S., Hill, T., Zuccaro, S.: Modeling power requirements for skid-steer mobile robots in manufacturing enviroments. In: ASME International Design Engineering Technical Conferences. Charlotte (2016)

  23. Bazzi, S., Shammas, E., Asmar, D.: A novel method for modeling skidding for systems with nonholonomic constraints. Nonlinear Dyn. 76(2), 1517–1528 (2014)

    Article  Google Scholar 

  24. O’Toole, A., Canfield, S.: Developing a kinematic estimation model for a climbing mobile robotic welding system. In: ASME International Design Engineering Technical Conferences. Montreal (2010)

  25. Kumar, P., Hill, T., Bryant, A., Canfield, S.: Modeling and design of a linkage-based suspension for tracked-type climbing mobile robotic systems. In: ASME International Design Engineering Technical Conferences. Washington (2011)

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Authors and Affiliations

  1. Tennessee Technological University, Brown Hall 224, 115 West 10th Street, Cookeville, TN, 38505, USA

    Stephen L. Canfield, Tristan W. Hill & Stephen G. Zuccaro

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  1. Stephen L. Canfield
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  2. Tristan W. Hill
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  3. Stephen G. Zuccaro
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Correspondence to Stephen L. Canfield.

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Canfield, S.L., Hill, T.W. & Zuccaro, S.G. Prediction and Experimental Validation of Power Consumption of Skid-Steer Mobile Robots in Manufacturing Environments. J Intell Robot Syst 94, 825–839 (2019). https://doi.org/10.1007/s10846-018-0779-7

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  • DOI: https://doi.org/10.1007/s10846-018-0779-7

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