Skip to main content
Log in

A Motion Planning Framework with Connectivity Management for Multiple Cooperative Robots

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This paper proposes a decentralized motion planning algorithm for multiple cooperative robots subject to constraints imposed by sensors and the communication network. It consists of decentralized receding horizon planners that reside on each vehicle to navigate to individual target positions. A routing algorithm which modify the network topology based on the position of the robots and the limited range of transmitters and receivers, enables to reduce the communication link failures. A comparative study between the proposed algorithm and other existing algorithms is provided in order to show the advantages especially in terms of traveling time and communication link failure.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Wurman, P.R., D’Andrea, R., Mountz, M.: Coordinating hundreds of cooperative autonomous vehicles in warehouses. AI Mag. 29, 9–20 (2008)

    Google Scholar 

  2. Herrero-Perez, D., Martinez-Barbera, H.: Decentralized traffic control for non-holonomic flexible automated guided vehicles in industrial environments. Adv. Robot 25, 739–763 (2011)

    Article  Google Scholar 

  3. Kolling, A., Carpin, S.: Multi-robot surveillance: an improved algorithm for the GRAPH-CLEAR problem. In: IEEE International Conference on Robotics and Automation, pp. 2360–2365 (2008)

  4. Kolling, A., Carpin, S.: Pursuit-Evasion on Trees by Robot Teams. IEEE Trans. Robot. 26, 32–47 (2010)

    Article  Google Scholar 

  5. Burgard, W., Moors, M., Stachniss, C., Schneider, F.E.: Coordinated multi-robot exploration. IEEE Trans. Robot. 21, 376–386 (2005)

    Article  Google Scholar 

  6. Purwin, O., D’Andrea, R., Lee, J.: Theory and implementation of path planning by negotiation for decentralized agents. Robot. Auton. Syst. 56, 422–436 (2008)

    Article  Google Scholar 

  7. Pereira, G., Kumar, V., Campos, M.: Closed loop motion planning of cooperating mobile robots using graph connectivity. Robot. Auton. Syst. 56, 373–384 (2008)

    Article  Google Scholar 

  8. Zavlanos, M., Pappas, G.: Distributed Connectivity Control of Mobile Networks. IEEE Trans. Robot. 24, 1416–1428 (2008)

    Article  Google Scholar 

  9. Dunbar, W., Murray, R.: Model predictive control of coordinated multi-vehicle formation. In: IEEE Conf. on Decision and Control (2002)

  10. Borrelli, F., Subramanian, D., Raghunathan, A., Biegler, L., Samad, T.: MILP and NLP techniques for centralized trajectory planning of multiple unmanned air vehicles. In: Proc. Amer. Control Conf (2006)

  11. Bennewitz, M., Burgard, W., Thrun, S.: Finding and optimizing solvable priority schemes for decoupled path planning techniques for teams of mobile robots. Robot. Auton. Syst. 41, 89–99 (2002)

    Article  Google Scholar 

  12. LaValle, S., Hutchinson, S.: Optimal motion planning for multiple robot having independant goals. IEEE Trans. Robot. Autom. 14, 912–925 (1998)

    Article  Google Scholar 

  13. Sanchez, G., Latombe, J.: On delaying collision checking in PRM planner to compare centralized and decoupled planning for multirobot systems. Int. J. Robot. Res. 21, 5–26 (2002)

    Article  Google Scholar 

  14. Masoud, A.: Decentralized, self-organizing, potential field-based control for individually-motivated, mobile agents in a cluttered environment: a vector-harmonic potential field approach. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 37, 372–390 (2007)

    Article  Google Scholar 

  15. Mayne, D., Rawlings, J., Rao, C., Scokaert, P.: Constrained model predicitive control: stability and optimality. Automatica 36(6), 789–814 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  16. Defoort, M., Palos, J., Kokosy, A., Floquet, T., Perruquetti, W.: Performance-based reactive navigation for nonholonomic mobile robots. Robotica 27, 281–290 (2009)

    Article  Google Scholar 

  17. Dunbar, W., Murray, R.: Distributed receding for multi-vehicle formation stabilization. Automatica 42, 549–558 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  18. Keviczky, T., Borelli, F., Balas, G.: Decentralized receding horizon control for large scale dynamically decoupled systems. Automatica 42, 2105–2115 (2006)

    Article  MATH  Google Scholar 

  19. Keviczky, T., Borelli, F., Fregene, K., Godbole, D., Balas, G.: Decentralized receding horizon control and coordination of autonomous vehicle formations. IEEE Trans. Control Syst. Technol. 16, 19–32 (2008)

    Article  Google Scholar 

  20. Kuwata, Y., Richards, A., Schouwenaars, T., How, J.: Distributed robust receding horizon control for multivehicle guidance. IEEE Trans. Control Syst. Technol. 15, 627–641 (2007)

    Article  Google Scholar 

  21. Defoort, M., Kokosy, A., Floquet, T., Perruquetti, W., Palos, J.: Motion planning for cooperative unicycle-type mobile robots with limited sensing ranges: a distributed receding horizon approach. Robot. Auton. Syst. 57, 1094–1106 (2009)

    Article  Google Scholar 

  22. Toh, C.K.: Ad Hoc Mobile Wireless Networks. Prentice Hall (2002)

  23. Lerman, K., Jones, C., Galstyan, A., Mataric, M.: Analysis of dynamic task allocation in multirobot systems. Int. J. Robot. Res. 25, 225–241 (2006)

    Article  Google Scholar 

  24. de Boor, C.: A Practical Guide to Splines. Springer-Verlag (1978)

  25. Defoort, M., Doniec, A., Bouraqadi, N.: Decentralized robust collision avoidance based on receding horizon planning and potential field for mult-robot system. In: Andrade Cetto, J., Filipe, J., Ferrier, J.-L. (eds.) Informatics in Control Automation and Robotics, Lecture Notes in Electrical Engineering, vol. 85, pp. 201–215. Springer (2011)

  26. Lawrence, C., Tits, A.: A computationally efficient feasible sequential quadratic programming algorithm. SIAM J. Optim. 11, 1092–1118 (2001)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael Defoort.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Defoort, M., Veluvolu, K.C. A Motion Planning Framework with Connectivity Management for Multiple Cooperative Robots. J Intell Robot Syst 75, 343–357 (2014). https://doi.org/10.1007/s10846-013-9872-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-013-9872-0

Keywords

Navigation