Skip to main content

Path Planning for Cooperating Unmanned Vehicles over 3-D Terrain

  • Chapter
Informatics in Control, Automation and Robotics

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 24))

Abstract

In this paper we suggest an off-line/on-line path planner for cooperating unmanned vehicles that takes into account the mission objectives and constraints through an optimization procedure. The cooperating vehicles can be either Unmanned Aerial Vehicles (UAVs) or Autonomous Underwater Vehicles (AUVs); these two categories of vehicles share common features as far as path planning is concerned and these features are used in this work for the development of a unified approach to the path planning problem over 3-D terrains. A number of unmanned vehicles of the same category are launched from the same or different known initial locations. The main issue is to produce 3-D trajectories (represented by 3-D B-Spline curves) that ensure a collision free path, respect the mission objectives and constraints, and guide the vehicles to a common final destination. The off-line planner is designed for known environments. The on-line one generates paths in unknown static environments, by exchanging acquired information from the cooperating vehicles’ on-board sensors. For each vehicle a near optimum path is generated that guides it safely to an intermediate position within the already scanned area. The process is repeated for each vehicle until the final destination is reached by one or more members of the team. Then, each one of the remaining vehicles can either turn into the off-line mode to reach the target, moving through the already scanned area, or continue with the on-line mode. Both off-line and on-line path planning problems are formulated as optimization problems, and a Differential Evolution algorithm is used as the optimizer.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gilmore, J.F.: Autonomous Vehicle Planning Analysis Methodology. In: Association of Unmanned Vehicles Systems Conference. Washington, DC, pp. 503–509 (1991)

    Google Scholar 

  2. LaValle, S.M.: Planning Algorithms. Cambridge University Press (2006)

    Google Scholar 

  3. Bortoff, S.: Path Planning for UAVs. In: Amer. Control Conf., Chicago, IL, pp. 364–368 (2000)

    Google Scholar 

  4. Szczerba, R.J., Galkowski, P., Glickstein, I.S., and Ternullo, N.: Robust Algorithm for Real-Time Route Planning. IEEE Trans. on Aerosp. Electr. Syst. 36, 869–878 (2000)

    Article  Google Scholar 

  5. Zheng, C., Li, L., Xu, F., Sun, F., Ding, M.: Evolutionary Route Planner for Unmanned Air Vehicles. IEEE Trans. on Rob. 21, 609–620 (2005)

    Article  Google Scholar 

  6. Uny Cao, Y., Fukunaga, A.S., Kahng, A.B.: Cooperative Mobile Robotics: Antecedents and Directions. Autonomous Robots, 4, 7–27(1997)

    Article  Google Scholar 

  7. Schumacher, C.: Ground Moving Target Engagement by Cooperative UAVs. In: 2005 American Control Conference, June 8-10, Portland, OR, USA (2005)

    Google Scholar 

  8. Mettler, B., Schouwenaars, T., How, J., Paunicka, J., and Feron E.: Autonomous UAV Guidance Build-up: Flight-Test Demonstration and Evaluation Plan. In: AIAA Guidance, Navigation, and Control Conference, AIAA-2003-5744 (2003)

    Google Scholar 

  9. Beard, R.W., McLain, T.W., Goodrich, M.A., Anderson, E.P.: Coordinated Target Assignment and Intercept for Unmanned Air Vehicles. IEEE Trans. on Rob. and Autom. 18 911–922 (2002)

    Article  Google Scholar 

  10. Richards, A., Bellingham, J., Tillerson, M., and How., J.: Coordination and Control of UAVs. In: AIAA Guidance, Navigation and Control Conference, Monterey, CA, (2002)

    Google Scholar 

  11. Schouwenaars, T., How, J., and Feron, E.: Decentralized Cooperative Trajectory Planning of Multiple Aircraft with Hard Safety Guarantees. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA-2004-5141 (2004)

    Google Scholar 

  12. Flint, M., Polycarpou, M., and Fernandez-Gaucherand, E.: Cooperative Control for Multiple Autonomous UAV’s Searching for Targets. In: 41st IEEE Conference on Decision and Control (2002)

    Google Scholar 

  13. Tang, Z., and Ozguner, U.: Motion Planning for Multi-Target Surveillance with Mobile Sensor Agents. IEEE Trans. on Rob. 21, 898–908 (2005)

    Article  Google Scholar 

  14. Gomez Ortega, J., and Camacho, E.F.: Mobile Robot Navigation in a Partially Structured Static Environment, using Neural Predictive Control. Control Eng. Practice, 4, 1669–1679 (1996)

    Article  Google Scholar 

  15. Kwon, Y.D., and Lee, J.S.: On-Line Evolutionary Optimization of Fuzzy Control System based on Decentralized Population. Intelligent Automation and Soft Computing, 6, 135–146 (2000)

    Google Scholar 

  16. Nikolos, I.K., Valavanis, K.P., Tsourveloudis, N.C., Kostaras, A.: Evolutionary Algorithm Based Offline / Online Path Planner for UAV Navigation. IEEE Trans. on Systems, Man, and Cybernetics – Part B: Cybernetics, 33, 898-912 (2003)

    Article  Google Scholar 

  17. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer (1999)

    Google Scholar 

  18. Smierzchalski, R.: Evolutionary Trajectory Planning of Ships in Navigation Traffic Areas. Journal of Marine Science and Technology, 4, 1–6 (1999)

    Article  Google Scholar 

  19. Smierzchalski, R., and Michalewicz Z.: Modeling of Ship Trajectory in Collision Situations by an Evolutionary Algorithm. IEEE Trans. on Evol. Comp. 4, 227–241 (2000)

    Article  Google Scholar 

  20. Sugihara, K., and Smith, J.: Genetic Algorithms for Adaptive Motion Planning of an Autonomous Mobile Robot. In: 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, Monterey, California, 138–143 (1997)

    Google Scholar 

  21. Sugihara, K., and Yuh, J.: GA-Based Motion Planning for Underwater Robotic Vehicles. UUST-10, Durham, NH (1997)

    Google Scholar 

  22. Shima, T., Rasmussen, S.J., Sparks, A.G.: UAV Cooperative Multiple Task Assignments using Genetic Algorithms. In: 2005 American Control Conference, June 8-10, Portland, OR, USA (2005)

    Google Scholar 

  23. Moitra, A., Mattheyses, R.M., Hoebel, L.J., Szczerba, R.J., Yamrom, B.: Multivehicle Reconnaissance Route and Sensor Planning. IEEE Trans. on Aerospace and Electronic Syst. 37, 799–812 (2003)

    Article  Google Scholar 

  24. Dubins, L.: On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Position. Amer. J. of Math. 79, 497–516 (1957)

    Article  MATH  MathSciNet  Google Scholar 

  25. Shima, T., Schumacher, C.: Assignment of Cooperating UAVs to Simultaneous Tasks Using Genetic Algorithms. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco (2005)

    Google Scholar 

  26. Martinez-Alfaro H., and Gomez-Garcia, S.: Mobile Robot Path Planning and Tracking using Simulated Annealing and Fuzzy Logic Control. Expert Systems with Applications, 15, 421–429 (1988)

    Article  Google Scholar 

  27. Nikolos, I.K., Tsourveloudis, N., and Valavanis, K.P.: Evolutionary Algorithm Based 3-D Path Planner for UAV Navigation. In: 9th Mediterranean Conference on Control and Automation, Dubrovnik, Croatia (2001)

    Google Scholar 

  28. Piegl, L., Tiller, W.: The NURBS Book. Springer (1997)

    Google Scholar 

  29. Farin, G.: Curves and Surfaces for Computer Aided Geometric Design, a Practical Guide. Academic Press (1988)

    Google Scholar 

  30. Price, K.V., Storn, R.M., Lampinen, J.A.: Differential Evolution, a Practical Approach to Global Optimization. Springer-Verlag, Berlin Heidelberg (2005)

    MATH  Google Scholar 

  31. Nikolos, I.K., Tsourveloudis, N., Valavanis, K.: Evolutionary Algorithm Based Path Planning for Multiple UAV Cooperation. In: Valavanis, K. (ed.), Advances in Unmanned Aerial Vehicles, State of the Art and the Road to Autonomy, pp. 309–340. Springer (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Nikolos, I.K., Tsourvelouds, N.C. (2009). Path Planning for Cooperating Unmanned Vehicles over 3-D Terrain. In: Filipe, J., Cetto, J.A., Ferrier, JL. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85640-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-85640-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85639-9

  • Online ISBN: 978-3-540-85640-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics