Causal Domain Restriction for Eikonal Equations

Many applications require efficient methods for solving continuous shortest path problems. Such paths can be viewed as characteristics of static Hamilton--Jacobi equations. Several fast numerical algorithms have been developed to solve such equations on the whole domain. In this paper, we consider a somewhat different problem, where the solution is needed at one specific point, so we restrict the computations to a neighborhood of the characteristic. We explain how heuristic under/over-estimate functions can be used to obtain a causal domain restriction, significantly decreasing the computational work without sacrificing convergence under mesh refinement. The discussed techniques are inspired by an alternative version of the classical A* algorithm on graphs. We illustrate the advantages of our approach on continuous isotropic examples in two and three dimensions. We compare its efficiency and accuracy to previous domain restriction techniques. We also analyze the behavior of errors under the grid refinemen...

[1]  J. Tsitsiklis,et al.  Efficient algorithms for globally optimal trajectories , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[2]  Stanley Bak,et al.  Some Improvements for the Fast Sweeping Method , 2010, SIAM J. Sci. Comput..

[3]  James A. Sethian,et al.  Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid , 2012 .

[4]  Alexander Vladimirsky,et al.  Label-Setting Methods for Multimode Stochastic Shortest Path Problems on Graphs , 2007, Math. Oper. Res..

[5]  M. Bardi,et al.  Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations , 1997 .

[6]  Laurent D. Cohen,et al.  Landmark-Based Geodesic Computation for Heuristically Driven Path Planning , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[7]  J. Sethian,et al.  Fast methods for the Eikonal and related Hamilton- Jacobi equations on unstructured meshes. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[8]  J. Sethian,et al.  Ordered upwind methods for static Hamilton–Jacobi equations , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[10]  M. L. Chambers The Mathematical Theory of Optimal Processes , 1965 .

[11]  G. Barles,et al.  Convergence of approximation schemes for fully nonlinear second order equations , 1990, 29th IEEE Conference on Decision and Control.

[12]  Adam Chacon Eikonal Equations: New Two-Scale Algorithms And Error Analysis , 2014 .

[13]  Hongkai Zhao,et al.  A fast sweeping method for Eikonal equations , 2004, Math. Comput..

[14]  Steven M. LaValle,et al.  Simplicial dijkstra and A* algorithms for optimal feedback planning , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  S. Zagatti On viscosity solutions of Hamilton-Jacobi equations , 2008 .

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

[17]  Peter Schlattmann,et al.  Theory and Algorithms , 2009 .

[18]  J A Sethian,et al.  A fast marching level set method for monotonically advancing fronts. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Clement Petres,et al.  Trajectory planning for autonomous underwater vehicles , 2010 .

[20]  Steven M. LaValle,et al.  Simplicial Dijkstra and A∗ Algorithms: From Graphs to Continuous Spaces , 2012, Adv. Robotics.

[21]  Alexander Vladimirsky,et al.  Ordered Upwind Methods for Static Hamilton-Jacobi Equations: Theory and Algorithms , 2003, SIAM J. Numer. Anal..

[22]  Roland Philippsen A Light Formulation of the E* Interpolated Path Replanner , 2006 .

[23]  Alexander Vladimirsky,et al.  Fast Two-scale Methods for Eikonal Equations , 2011, SIAM J. Sci. Comput..

[24]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[25]  Laurent D. Cohen,et al.  Heuristically Driven Front Propagation for Geodesic Paths Extraction , 2005, VLSM.

[26]  Maurizio Falcone,et al.  A Patchy Dynamic Programming Scheme for a Class of Hamilton-Jacobi-Bellman Equations , 2011, SIAM J. Sci. Comput..

[27]  E. Rouy,et al.  A viscosity solutions approach to shape-from-shading , 1992 .

[28]  Andrew V. Goldberg,et al.  Computing the shortest path: A search meets graph theory , 2005, SODA '05.

[29]  R. Newcomb VISCOSITY SOLUTIONS OF HAMILTON-JACOBI EQUATIONS , 2010 .

[30]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[31]  Anthony Stentz,et al.  Field D*: An Interpolation-Based Path Planner and Replanner , 2005, ISRR.