Large-scale path planning for Underwater Gliders in ocean currents

Underwater gliders are a class of AUVs designed for high endurance over long distances, but their reduced velocity makes them more susceptible to ocean currents during deployment. Thus, feasible paths need to be generated through the ocean current field. This paper proposes a method for determining energy-optimal paths that account for the influence of ocean currents. The proposed technique is based on Rapidly-Exploring Random Trees (RRTs). Using real ocean current and bathymetry data, results produce comparable paths to grid based methods, and offer an improvement in terms of avoiding high-energy shallow regions. Future work will focus on heuristically biasing the RRT growth to further improve the generated paths, and implementation of the algorithms on a glider platform.

[1]  Jerrold E. Marsden,et al.  Optimal trajectory generation for a glider in time-varying 2D ocean flows B-spline model , 2008, 2008 IEEE International Conference on Robotics and Automation.

[2]  Joshua Grady Graver,et al.  UNDERWATER GLIDERS: DYNAMICS, CONTROL AND DESIGN , 2005 .

[3]  Roy M. Turner,et al.  The Development of Autonomous Underwater Vehicles (AUV); A Brief Summary , 2001 .

[4]  Steven M. LaValle,et al.  Randomized Kinodynamic Planning , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[5]  Rubo Zhang,et al.  Research on Global Path Planning in the Marine Environment for AUV , 2007 .

[6]  S.C. Shadden,et al.  Optimal trajectory generation in ocean flows , 2005, Proceedings of the 2005, American Control Conference, 2005..

[7]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[8]  S. LaValle,et al.  Randomized Kinodynamic Planning , 2001 .

[9]  Gabriel Oliver,et al.  Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: an A* Approach , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[10]  Nina Mahmoudian,et al.  Steady Turns and Optimal Paths for Underwater Gliders , 2007 .

[11]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[12]  E. L. Nelson,et al.  AUV path planning: an A* approach to path planning with consideration of variable vehicle speeds and multiple, overlapping, time-dependent exclusion zones , 1992, Proceedings of the 1992 Symposium on Autonomous Underwater Vehicle Technology.

[13]  Robert Sutton,et al.  An incremental stochastic motion planning technique for autonomous underwater vehicles , 2004 .

[14]  S. LaValle Rapidly-exploring random trees : a new tool for path planning , 1998 .

[15]  Reid G. Simmons,et al.  Approaches for heuristically biasing RRT growth , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[16]  Matthew Dunbabin,et al.  Go with the flow : optimal AUV path planning in coastal environments , 2009, ICRA 2009.