Skip to main content

Advertisement

SpringerLink
Log in

Dynamically feasible, energy efficient motion planning for skid-steered vehicles

  • Published:
Autonomous Robots Aims and scope Submit manuscript

Abstract

Recent research has developed experimentally verified dynamic models for skid-steered wheeled vehicles and used these results to derive a power model for this important class of all-terrain vehicles. As presented in this paper, based on the torque limitations of the vehicle motors, the dynamic model can be used to develop payload and terrain-dependent minimum turn radius constraints and the power model can be used to predict the energy consumption of a given trajectory. This paper uses these results along with sampling based model predictive optimization to develop an effective methodology for generating dynamically feasible, energy efficient trajectories for skid-steered autonomous ground vehicles (AGVs) and compares the resultant trajectories with those based on the standard distance optimal trajectories. The simulated and experimental results consider an AGV moving at a constant forward velocity on both wood and asphalt surfaces under various payloads. The results show that a small increase in the distance of a trajectory over the distance optimal trajectory can result in a dramatic savings in the AGV’s energy consumption. They also show that distance optimal planning can often produce trajectories that violate the motor torque constraints for skid-steered AGVs, which can result in poor navigation performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28

Similar content being viewed by others

Notes

  1. A modular wooden surface was used because it can be attached to a variable slope in the authors’ lab for future experiments that focus on sloped surfaces.

  2. This paper has supplementary downloadable material (Motion_planning.zip) showing the motion planning results for movement on both wood and asphalt surfaces as presented in this paper.

References

  • Barili, A., Ceresa, M., & Parisi, C. (1995). Energy saving motion control for an autonomous mobile robot. In Proceedings of the International Symposium on Industrial Electronics (pp. 674–676).

  • Caldwell, C., Dunlap, D., & Collins, E.G.J. (2010). Motion planning for an autonomous underwater vehicle via sampling based model predictive control. In OCEANS 2010 (pp. 1–6).

  • Caracciolo, L., De Luca, A., & Iannitti, S. (1999). Trajectory tracking control of a four-wheel differentially driven mobile robot. In Proceedings 1999 IEEE International Conference on Robotics and Automation, 1999, volume 4 (pp 2632–2638).

  • Chuy, O., Collins, E., Dunlap, D., & Sharma, A. (2013). Sampling-based direct trajectory generation using the minimum time cost function. In Experimental Robotics, Springer Tracts in Advanced Robotics, volume 88 (pp. 651–666). Springer International Publishing.

  • Collins, E., Yu, W., Chuy, O., & Gupta, N. (2011). Dynamic and power modeling for skid-steered vehicles. In NSF Engineering Research and Innovation Conference.

  • Dunlap, D.D., Caldwell, C.V., & Collins, E.G.J. (2010). Nonlinear model predictive control using sampling and goal-directed optimization. In IEEE Conference on Control Applications (pp. 1349–1356).

  • Dunlap, D.D., Caldwell, C.V., Collins, E.G.J., & Chuy, O. (2011a). Motion planning for mobile robots via sampling-based model predictive optimization. Intech.

  • Dunlap, D., Yu, W., Collins, J.E.G., & Caldwell, C. (2011b). Motion planning for steep hill climbing. In 2011 IEEE International Conference on Robotics and Automation (ICRA) (pp. 707–714).

  • Dyer, C. (2002). Fuel cells for portable applications. Fuel Cell Bulletin, 2002, 8–9.

    Article  Google Scholar 

  • Ericson, C. (2005). Real-time collision detection. San Francisco, CA: Elsevier.

    Google Scholar 

  • Hwang, Y., & Ahuja, N. (1992). Gross motion planning—a survey. ACM Computing Surveys, 24, 219–291.

    Article  Google Scholar 

  • Karaman, S., & Frazzoli, E. (2011). Sampling-based algorithms for optimal motion planning. The International Journal of Robotics Research, 30(7), 846–894.

    Article  MATH  Google Scholar 

  • Kozlowski, K., & Pazderski, D. (2004). Modeling and control of a 4-wheel skid-steering mobile robot. International Journal of Mathematics and Computer Science, 14, 477–496.

    MathSciNet  MATH  Google Scholar 

  • Likhachev, M., & Ferguson, D. (2009). Planning long dynamically feasible maneuvers for autonomous vehicles. The International Journal of Robotics Research, 28(8), 933–945.

    Article  Google Scholar 

  • Mandow, A., Martinez, J., Morales, J., Blanco, J.L., Garcia-Cerezo, A., & Gonzalez, J. (2007). Experimental kinematics for wheeled skid-steer mobile robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007 (pp. 1222–1227).

  • Martinez, J. L., Mandow, A., Morales, J., Pedraza, S., & Garca-Cerezo, A. (2005). Approximating kinematics for tracked mobile robots. The International Journal of Robotics Research, 24(10), 867–878.

    Article  Google Scholar 

  • Mei, Y., Lu, Y.H., Hu, Y., & Lee, C.S.G. (2004). Energy-efficient motion planning for mobile robots. In 2004 IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04, volume 5 (pp. 4344–4349).

  • Mei, Y., Lu, Y., Hu, Y., & Lee, C. (2006). Deployment of mobile robots with energy and timing constraints. EEE Transactions on Robotics, 22, 507–522.

    Article  Google Scholar 

  • Moosavian, S., & Kalantari, A. (2008). Experimental slip estimation for exact kinematics modeling and control of a tracked mobile robot. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. IROS 2008 (pp. 95–100).

  • Ordonez, C., Gupta, N., Collins, Jr. E.G., Clark, J.E., & Johnson, A.M. (2012a). Power modeling of the xrl hexapedal robot and its application to energy efficient motion planning. In Proceedings of the 15th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, volume 23 (p. 26). World Scientific.

  • Ordonez, C., Gupta, N., Yu, W., Chuy, O., Collins, E. (2012b). Modeling of skid-steered wheeled robotic vehicles on sloped terrains. In Proceedings of the ASME Dynamic Systems and Control Conference (pp. 91–99).

  • Ordonez, C., Gupta, N., Chuy, O., & Collins, E.G. (2013). Momentum based traversal of mobility challenges for autonomous ground vehicles. In 2013 IEEE International Conference on Robotics and Automation (ICRA) (pp. 752–759).

  • Perez, T., & Wesley, M. (1979). An algorithm for planning collision-free paths among polyhedral obstacles. Communications of the ACM, 22, 560–570.

    Article  Google Scholar 

  • Reese, B. (2015). A graph based approach to nonlinear model predictive control with application to combustion control and flow control. PhD Thesis Florida State University, Tallahassee, FL.

  • Schwartz, J., & Sharir, M. (1988). A survey of motion planning and related geometric algorithms. Artificial Intelligence Journal, 37, 157–169.

    Article  MathSciNet  MATH  Google Scholar 

  • Seegmiller, N., Rogers-Marcovitz, F., Miller, G., & Kelly, A. (2013). Vehicle model identification by integrated prediction error minimization. The International Journal of Robotics Research, 32(8), 912–931.

    Article  Google Scholar 

  • Tekscan (2010). Tire footprint pressure measurement. http://www.tekscan.com/industrial/tirescan-system.html.

  • Wong, J. Y. (2001). Theory of ground vehicles (3rd ed.). New. York: Wiley.

    Google Scholar 

  • Wong, J. Y., & Chiang, C. F. (2001). A general theory for skid steering of tracked vehicles on firm groun. Proceedings of the Institution of Mechanical Engineers Part D Journal of Automotive Engineering, 215, 343–355.

    Article  Google Scholar 

  • Yi, J., Song, D., Zhang, J., & Goodwin, Z. (2007). Adaptive trajectory tracking control of skid-steered mobile robots. In Proceedings of the International Conference on Robotics and Automation (pp. 2605–2610). Roma, Italy.

  • Yi, J., Wang, H., Zhang, J., Song, D., Jayasuriya, S., & Liu, J. (2009). Kinematic modeling and analysis of skid-steered mobile robots with applications to low-cost inertial-measurement-unit-based motion estimation. IEEE Transactions on Robotics, 25(5), 1087–1097.

    Article  Google Scholar 

  • Yu, W., Chuy, O., Collin, E. G., & Hollis, P. (2010). Analysis and experimental verification for dynamic modeling of a skid-steered wheeled vehicle. IEEE Transactions on Robotics, 26, 340–353.

    Article  Google Scholar 

  • Yu, W., Collins, E., & Chuy, O. (2011). Dynamic modeling and power modeling of robotic skid-steered wheeled vehicles. Intech.

Download references

Acknowledgments

This work was supported by the collaborative participation in the Robotics Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD 19-01-2-0012. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes not withstanding any copyright notation thereon.

Author information

Authors and Affiliations

  1. Center for Intelligent Systems, Controls and Robotics (CISCOR) and the Department of Mechanical Engineering, Florida A&M University-Florida State University, Tallahassee, FL, 32310, USA

    Nikhil Gupta, Camilo Ordonez & Emmanuel G. Collins Jr.

Authors
  1. Nikhil Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Camilo Ordonez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emmanuel G. Collins Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nikhil Gupta.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (mpg 49587 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, N., Ordonez, C. & Collins, E.G. Dynamically feasible, energy efficient motion planning for skid-steered vehicles. Auton Robot 41, 453–471 (2017). https://doi.org/10.1007/s10514-016-9550-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10514-016-9550-8

Keywords

Search

Navigation