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Target following with motion prediction for unmanned surface vehicle operating in cluttered environments

Abstract

The capability of following a moving target in an environment with obstacles is required as a basic and necessary function for realizing an autonomous unmanned surface vehicle (USV). Many target following scenarios involve a follower and target vehicles that may have different maneuvering capabilities. Moreover, the follower vehicle may not have prior information about the intended motion of the target boat. This paper presents a trajectory planning and tracking approach for following a differentially constrained target vehicle operating in an obstacle field. The developed approach includes a novel algorithm for computing a desired pose and surge speed in the vicinity of the target boat, jointly defined as a motion goal, and tightly integrates it with trajectory planning and tracking components of the entire system. The trajectory planner generates a dynamically feasible, collision-free trajectory to allow the USV to safely reach the computed motion goal. Trajectory planning needs to be sufficiently fast and yet produce dynamically feasible and short trajectories due to the moving target. This required speeding up the planning by searching for trajectories through a hybrid, pose-position state space using a multi-resolution control action set. The search in the velocity space is decoupled from the search for a trajectory in the pose space. Therefore, the underlying trajectory tracking controller computes desired surge speed for each segment of the trajectory and ensures that the USV maintains it. We have carried out simulation as well as experimental studies to demonstrate the effectiveness of the developed approach.

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References

  1. Aguiar, A., Almeida, J., Bayat, M., Cardeira, B., Cunha, R., Häusler, A., Maurya, P., Oliveira, A., Pascoal, A. & Pereira, A. et al. (2009). Cooperative control of multiple marine vehicles. In Proceedings of 8th IFAC international conference on manoeuvering and control of marine craft (pp. 16–18).

  2. Alves, J., Oliveira, P., Oliveira, R., Pascoal, A., Rufino, M., Sebastiao, L., & Silvestre, C. (2006). Vehicle and mission control of the delfim autonomous surface craft. In: 14th Mediterranean conference on control and automation (MED’06) (pp. 1–6).

  3. Ashrafiuon, H., Muske, K. R., & McNinch, L. C. (2010). Review of nonlinear tracking and setpoint control approaches for autonomous underactuated marine vehicles. In American Control Conference (ACC’10) (pp. 5203–5211).

  4. Benjamin, M. R., Curcio, J. A., & Newman, P. M. (2006). Navigation of unmanned marine vehicles in accordance with the rules of the road. In IEEE international conference on robotics and automation (ICRA’06) (pp. 3581–3587).

  5. Bennewitz, M., Burgard, W., & Thrun, S. (2002). Finding and optimizing solvable priority schemes for decoupled path planning techniques for teams of mobile robots. Robotics and autonomous systems, 41(2–3), 89–99.

  6. Bertram, V. (2008). Unmanned surface vehicles-a survey. Copenhagen: Denmark: Skibsteknisk Selskab.

  7. Bertaska, I.R., Alvarez, J., Armando, S., von Ellenrieder, K.D., Dhanak, M., Shah, B. et al. (2013). Experimental evaluation of approach behavior for autonomous surface vehicles. In ASME Dynamic Systems and Control Conference (DSCC’13), Stanford University, Palo Alto, October 21–23.

  8. Bibuli, M., Bruzzone, G., Caccia, M., & Lapierre, L. (2009). Path-following algorithms and experiments for an unmanned surface vehicle. Journal of Field Robotics, 26(8), 669–688.

  9. Bibuli, M., Caccia, M., Lapierre, L., & Bruzzone, G. (2012). Guidance of unmanned surface vehicles: Experiments in vehicle following. IEEE Robotics and Automation Magazine, 99, 1–11.

  10. Borrelli, F., Subramanian, D., Raghunathan, A.U., & Biegler, L.T. (2006). MILP and NLP techniques for centralized trajectory planning of multiple unmanned air vehicles. In American Control Conference (p. 6).

  11. Breivik, M. (2010). Topics in guided motion control of marine vehicles. PhD thesis, Norwegian University of Science and Technology.

  12. Breivik, M., Hovstein, V. E., & Fossen, T. I. (2008). Straight-line target tracking for unmanned surface vehicles. Modeling Identification and Control, 29(4), 131–149.

  13. Breivik, M., Hovstein, V. E., & Fossen, T. I. (2008). Ship formation control: A guided leader-follower approach. In World Congress, 17, 16008–16014.

  14. Caccia, M., Bibuli, M., Bono, R., & Bruzzone, G. (2008). Basic navigation, guidance and control of an unmanned surface vehicle. Autonomous Robots, 25(4), 349–365.

  15. Casalino, G., Turetta, A., & Simetti E. (2009). A three-layered architecture for real time path planning and obstacle avoidance for surveillance usvs operating in harbour fields. In OCEANS’09 (pp. 1–8).

  16. Chung, T. H., Hollinger, G. A., & Isler, V. (2011). Search and pursuit-evasion in mobile robotics. Autonomous Robots, 40, 1–18.

  17. Colombo, C., Vasile, M., & Radice, G. (2009). Optimal low-thrust trajectories to asteroids through an algorithm based on differential dynamic programming. Celestial Mechanics and Dynamical Astronomy, 105, 75–112.

  18. Corfield, S.J., & Young, J.M. (2006). Unmanned surface vehicles-game changing technology for naval operations. Advances in unmanned marine vehicles (pp. 311–328).

  19. Curcio, J., Leonard, J., & Patrikalakis, A. (2005). Scout-a low cost autonomous surface platform for research in cooperative autonomy (pp. 725–729). OCEANS: In Proceedings of MTS/IEEE.

  20. Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische mathematik, 1(1), 269–271.

  21. Do, K. D., Jiang, Z. P., & Pan, J. (2002). Underactuated ship global tracking under relaxed conditions. IEEE Transactions on Automatic Control, 47(9), 1529–1536.

  22. Donald, B., Xavier, P., Canny, J., & Reif, J. (1993). Kinodynamic motion planning. Journal of ACM, 40, 1048–1066.

  23. Earl, M. G., & D’Andrea, R. (2005). Iterative MILP methods for vehicle-control problems. IEEE Transactions on Robotics, 21(6), 1158–1167.

  24. Ebken, J. (2005). Applying unmanned ground vehicle technologies to unmanned surface vehicles. DTIC Document: Technical report.

  25. Eickstedt, D. P., Benjamin, M. R., & Curcio J. (2007). Behavior based adaptive control for autonomous oceanographic sampling. In IEEE international conference on robotics and automation (pp. 4245–4250).

  26. Elnagar, A., & Hussein, A. (2000). On optimal constrained trajectory planning in 3d environments. Robotics and Autonomous Systems, 33(4), 195–206.

  27. Erickson, L. H., & LaValle, S. M., (2009). Survivability: Measuring and ensuring path diversity. In IEEE international conference on robotics and automation (ICRA’09) (pp. 2068–2073).

  28. Fiorini, P., & Shiller, Z. (1998). Motion planning in dynamic environments using velocity obstacles. The International Journal of Robotics Research, 17(7), 760–772.

  29. Fossen, T. I. (1994). Guidance and control of ocean vehicles. Chicester: Wiley.

  30. Fossen, T. I. (2011). Handbook of marine craft hydrodynamics and motion control. Chichester: Wiley.

  31. Frazzoli, E., Dahleh, M.A., & Feron E. (1999). A hybrid control architecture for aggressive maneuvering of autonomous helicopters. In Proceedings of the 38th IEEE conference on decision and, control, vol. 3 (pp 2471–2476).

  32. Frazzoli, E., Dahleh, M. A., & Feron, E. (2001). Real-time motion planning for agile autonomous vehicles. Proceedings of the 2001 American Control Conference, 1, 43–49.

  33. Furfaro, T. C., Dusek, J. E. & von Ellenrieder, K. D. (2009). Design, construction, and initial testing of an autonomous surface vehicle for riverine and coastal reconnaissance. In OCEANS 2009, MTS/IEEE Biloxi-marine technology for our future: Global and local, challenges (pp. 1–6).

  34. Goerzen, C., Kong, Z., & Mettler, B. (2010). A survey of motion planning algorithms from the perspective of autonomous UAV guidance. Journal of Intelligent Robotic Systems, 57, 65–100. doi:10.1007/s10846-009-9383-1.

  35. Graham, M. M. (2008). Unmanned surface vehicles: An operational commander’s tool for maritime security. DTIC Document: Technical report.

  36. Green. C. J., & Kelly, A. (2007). Toward optimal sampling in the space of paths. In 13th International symposium of robotics research.

  37. Greytak, M., & Hover, F. (2009). Motion planning with an analytic risk cost for holonomic vehicles. In Proceedings of the 48th IEEE conference on decision and control held jointly with the 2009 28th Chinese control conference (CDC/CCC’09) (pp. 5655– 5660).

  38. Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4(2), 100–107.

  39. Healey, A. J., & Lienard, D. (1993). Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles. IEEE Journal of Oceanic Engineering, 18(3), 327–339.

  40. Howard, T., & Kelly, A. (2007). Optimal rough terrain trajectory generation for wheeled mobile robots. International Journal of Robotics Research, 26(1), 141–166.

  41. Hsu, D., Kindel, R., Latombe, J. C., & Rock, S. (2002). Randomized kinodynamic motion planning with moving obstacles. The International Journal of Robotics Research, 21(3), 233–255.

  42. Huntsberger, T., Aghazarian, H., Castano, A., Woodward, G., Padgett, C., Gaines, D., et al. (2008). Intelligent autonomy for unmanned sea surface and underwater vehicles. In AUVSI Unmanned Systems North America.

  43. Huntsberger, T., Aghazarian, H., Gaines, D., Garrett, M., & Sibley, G. (2007). Autonomous operation of unmanned surface vehicles (usv’s). IEEE ICRA workshop on robots in challenging and hazardous environments: In Proceedings.

  44. Jean-Yves, B. (2010). Camera calibration toolbox for Matlab. 2010. Available at http://www.vision.caltech.edu/bouguetj/calib_doc.

  45. Katebi, M. R., Grimble, M. J., & Zhang, Y. (1997). H \(\infty \) robust control design for dynamic ship positioning. IEEE Proceedings on Control Theory and Applications, 144(2), 110–120.

  46. Kelly, A., Stentz, A., Amidi, O., Bode, M., Bradley, D., Diaz-Calderon, A., et al. (2006). Toward reliable off road autonomous vehicles operating in challenging environments. The International Journal of Robotics Research, 25(5–6), 449–483.

  47. Kilgore, R. M., Harper, K. A., Nehme, C., & Cummings, M. L. (2007). Mission planning and monitoring for heterogeneous unmanned vehicle teams: A human-centered perspective. In AIAA Infotech@ Aerospace Conference in Sonoma, CA.

  48. Krishnamurthy, P., Khorrami, F., & Fujikawa, S. (2005). A modeling framework for six degree-of-freedom control of unmanned sea surface vehicles. In Proceedings and 2005 European control conference decision and control CDC-ECC ’05. 44th IEEE Conference on decision and control (pp. 2676–2681), December 12–15.

  49. Kuwata, Y., Wolf, M.T., Zarzhitsky, D., & Huntsberger, T.L. (2011). Safe maritime navigation with colregs using velocity obstacles. In IEEE/RSJ international conference on intelligent robots and systems (IROS’11) (pp. 4728–4734).

  50. Larson, A. J., Bruch, M., & Ebken, J. (2006). Autonomous navigation and obstacle avoidance for unmanned surface vehicles. In SPIE Proceecings 6230: Unmanned Systems Technology VIII (pp. 17–20).

  51. Larson, J., Bruch, M., & Ebken, J. (2006). Autonomous navigation and obstacle avoidance for unmanned surface vehicles. DTIC Document: Technical report.

  52. LaValle, S.M. (2006). Planning algorithms. Cambridge: Cambridge University Press. Available at http://planning.cs.uiuc.edu.

  53. LaValle, S. M., & Kuffner, J. J. (2001). Randomized kinodynamic planning. The International Journal of Robotics Research, 20(5), 378–400.

  54. Lavalle, S. M., & Konkimalla, P. (2001). Algorithms for computing numerical optimal feedback motion strategies. The International Journal of Robotics Research, 20(9), 729–752.

  55. Lefeber, E., Pettersen, K. Y., & Nijmeijer, H. (2003). Tracking control of an underactuated ship. IEEE Transactions on Control Systems Technology, 11(1), 52–61.

  56. Li, Y., & Xiao, J. (2009) On-line planning of nonholonomic trajectories in crowded and geometrically unknown environments. In IEEE international conference on robotics and automation (ICRA’09) (pp. 3230–3236).

  57. Loria, A., Fossen, T. I., & Panteley, E. (2000). A separation principle for dynamic positioning of ships: Theoretical and experimental results. IEEE Transactions on Control Systems Technology, 8, 332–343.

  58. Majohr, J., & Buch, T. (2006). Modelling, simulation and control of an autonomous surface marine vehicle for surveying applications measuring dolphin messin. IEE Control Engineering Series, 69, 329.

  59. Manley, J. E. (2008). Unmanned surface vehicles, 15 years of development. In OCEANS (pp. 1–4).

  60. Mazenc, F., Pettersen, K., & Nijmeijer, H. (Oct 2002). Global uniform asymptotic stabilization of an underactuated surface vessel. IEEE Transactions on Automatic Control, 47(10), 1759–1762.

  61. Murphy, R. R., Steimle, E., Griffin, C., Cullins, C., Hall, M., & Pratt, K. (2008). Cooperative use of unmanned sea surface and micro aerial vehicles at hurricane wilma. Journal of Field Robotics, 25(3), 164–180.

  62. Naeem, W., Sutton, R., & Chudley, J. (2006). Modelling and control of an unmanned surface vehicle for environmental monitoring. Glasgow: In UKACC International Control Conference.

  63. Naeem, W., Xu, T., Sutton, R., & Tiano, A. (2008). The design of a navigation, guidance, and control system for an unmanned surface vehicle for environmental monitoring. Proceedings of the Institution of Mechanical Engineers Part M, 222(2), 67.

  64. Naeem, W., Irwin, G. W., & Yang, A. (2011). Colregs-based collision avoidance strategies for unmanned surface vehicles. Mechatronics, 0(6), 669–678.

  65. Pascoal, A., Silvestre, C., & Oliveira, P. (2006). Vehicle and mission control of single and multiple autonomous marine robots. IEE Control Engineering Series, 69, 353.

  66. Peng, Z., Wang, D., Chen, Z., Hu, X., & Lan, W. (2013). Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics. IEEE Transactions on Control Systems Technology, 99, 1–8.

  67. Pivtoraiko, M. (2012). Differentially constrained motion planning with state lattice motion primitives. PhD thesis, Pittsburgh: Robotics Institute, Carnegie Mellon University.

  68. Pivtoraiko, M., & Kelly, A. (2005). Generating near minimal spanning control sets for constrained motion planning in discrete state spaces. In IEEE/RSJ international conference on intelligent robots and systems (IROS’05) (pp. 3231–3237).

  69. Pivtoraiko, M., Nesnas, I. A. D., & Alonzo, K. (2009). Autonomous robot navigation using advanced motion primitives. In IEEE aerospace conference (pp. 1–7).

  70. Pivtoraiko, M., Knepper, R. A., & Kelly, A. (2009). Differentially constrained mobile robot motion planning in state lattices. Journal of Field Robotics, 26(3), 308–333.

  71. Purwin, O., & Andrea, R. (2006). Trajectory generation and control for four wheeled omnidirectional vehicles. Robotics and Autonomous Systems, 54(1), 13–22.

  72. Raboin, E., Švec, P., Nau, D. S., & Gupta, S. K. (2013). Model-predictive target defense by team of unmanned surface vehicles operating in uncertain environments. In IEEE International Conference on Robotics and Automation (ICRA’13), Germany, May 6–10.

  73. Richards, A., & How, J. P. (2002). Aircraft trajectory planning with collision avoidance using mixed integer linear programming. In Proceedings of the 2002 American Control Conference (ACC’02), Vol. 3 (pp. 1936–1941).

  74. Russell, S., & Norvig, P. (2009). Artificial intelligence: A modern approach. Englewood Cliffs: Prentice Hall.

  75. Ryan, J. P., Johnson, S. B. A., Sherman, K., & Rajan, F. (2010). Mobile autonomous process sampling within coastal ocean observing systems. Limnology and Oceanography Methods, 8, 394–402.

  76. Sandler, M., Wahl, A., Zimmermann, R., Faul, M., Kabatek, U., & Gilles, E. D. (1996). Autonomous guidance of ships on waterways. Robotics and Autonomous Systems, 18(3), 327–335.

  77. Scherer, S., Singh, S., Chamberlain, L., & Saripalli S. (2007). Flying fast and low among obstacles. In IEEE international conference on robotics and automation (ICRA’07) (pp. 2023–2029).

  78. Shafer, A. J., Benjamin, M. R., Leonard, J. J., & Curcio, J. (2008). Autonomous cooperation of heterogeneous platforms for sea-based search tasks. In Proceedings of MTS/IEEE OCEANS (pp. 1–10).

  79. Simetti, E., Turetta, A., Casalino, M., Storti, E., & Cresta, M. (2010). Protecting assets within a civilian harbour through the use of a team of usvs: Interception of possible menaces. In IARP workshop on robots for risky interventions and environmental surveillance-maintenance (RISE’10), Sheffield.

  80. Simetti, E. Turetta, A., Casalino, G., Storti, E., & Cresta, M. (2009). Towards the use of a team of USVs for civilian harbour protection: Real time path planning with avoidance of multiple moving obstacles. In IEEE 3rd workshop on planning, perception and navigation for intelligent vehicles (IROS’09), St. Louis.

  81. Soltan, R. A., Ashrafiuon, H., & Muske, K.R. (2009). State-dependent trajectory planning and tracking control of unmanned surface vessels. In American Control Conference (ACC’09) (pp. 3597–3602).

  82. Steimle, E. T. & Hall, M. L. (2006). Unmanned surface vehicles as environmental monitoring and assessment tools. In OCEANS (pp. 1–5).

  83. Sturm, P. F., & Maybank, S. J. (1999). On plane-based camera calibration: A general algorithm, singularities, applications. In IEEE computer society conference on computer vision and pattern recognition, Vol. 1.

  84. Suzuki, S. (2005). Online four-dimensional flight trajectory search and its flight testing. AIAA GNC Conference and Exhibit.

  85. Švec, P., Schwartz, M., Thakur, A., & Gupta, S.K. (2011). Trajectory planning with look-ahead for unmanned sea surface vehicles to handle environmental disturbances. In IEEE/RSJ International conference on intelligent robots and systems (IROS’11), San Francisco, CA, September 25–30. doi:10.1109/IROS.2010.5650385.

  86. Švec, P., Thakur, A., Shah, B.C., & Gupta, S.K. (2012).USV trajectory planning for time varying motion goal in an environment with obstacles. In ASME mechanisms and robotics conference, Chicago, August 12–15.

  87. Švec, P., Shah, B.C., Bertaska, I.R., Alvarez, J., Sinisterra, A.J., Ellenrieder, K von., et al. (2013). Dynamics-Aware Target Following for an Autonomous Surface Vehicle Operating under COLREGs in Civilian Traffic. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’13), Tokyo, November 3–7.

  88. Švec, P., & Gupta, S. K. (2012). Automated synthesis of action selection policies for unmanned vehicles operating in adverse environments. Autonomous Robots, 32(2), 149–164.

  89. Thakur, A., Švec, P., & Gupta, S. K. (2012). GPU based generation of state transition models using simulations for unmanned surface vehicle trajectory planning. Robotics and Autonomous Systems, 60(12), 1457–1471.

  90. Thakur, A., & Gupta, S. K. (2011). Real-time dynamics simulation of unmanned sea surface vehicle for virtual environments. Journal of Computing and Information Science in Engineering, 11(3), 031005.

  91. Thierry, Fraichard, & Hajime, Asama. (2004). Inevitable collision states a step towards safer robots? Advanced Robotics, 18(10), 1001–1024.

  92. Thrun, S., & Burgard, W. (2005). Probabilistic robotics. Cambridge: MIT Press.

  93. Xu, B., Kurdila, A. & Stilwell, D. J. (2009). A hybrid receding horizon control method for path planning in uncertain environments. In IEEE/RSJ international conference on intelligent robots and systems (IROS’09) (pp. 4887–4892).

  94. Yan, R., Pang, S., Sun, H., & Pang, Y. (2010). Development and missions of unmanned surface vehicle. Journal of Marine Science and Application, 9(4), 451–457.

  95. Zohar, I., Ailon, A., & Rabinovici, R. (2011). Mobile robot characterized by dynamic and kinematic equations and actuator dynamics: Trajectory tracking and related application. Robotics and Autonomous Systems, 59(6), 343–353.

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Acknowledgments

This work was supported by the U.S. Office of Naval Research under Grants N00014-10-1-0585 and N00014-12-1-0494, managed by R. Brizzolara. Opinions expressed in this paper are those of the authors and do not necessarily reflect opinions of the sponsors. In addition, we would like to thank Dr. David Akin for allowing us to perform experiments in the Neutral Buoyancy Research Facility (NBRF) at the University of Maryland.

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Correspondence to Petr Švec.

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Švec, P., Thakur, A., Raboin, E. et al. Target following with motion prediction for unmanned surface vehicle operating in cluttered environments. Auton Robot 36, 383–405 (2014). https://doi.org/10.1007/s10514-013-9370-z

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Keywords

  • Unmanned surface vehicle (USV)
  • Follow behavior
  • Motion prediction
  • Trajectory planning
  • Trajectory tracking