Shortest path planning on topographical maps

This paper introduces a new algorithm for quickly answering repetitive least-cost queries between pairs of points on the Earth's surface as represented by digital topographical maps. The algorithm uses a three-step process; preprocessing, geometrically modified Dijkstra search, and postprocessing. The preprocessing step computes and saves highly valuable global information that describes the underlying geometry of the terrain. The search step solves shortest path queries using a modified Dijkstra algorithm that takes advantage of the preprocessed information to "jump" quickly across flat terrain and decide whether a path should go over or through a high-cost region. The final step is a path improvement process that straightens and globally improves the path. Our algorithm partitions the search space into free regions and obstacle regions. However, unlike other algorithms using this approach, our algorithm keeps the option of passing through an obstacle region.

[1]  Hans P. Moravec Robot Rover Visual Navigation , 1981 .

[2]  James L. Crowley,et al.  Navigation for an intelligent mobile robot , 1985, IEEE J. Robotics Autom..

[3]  Judea Pearl,et al.  Heuristics : intelligent search strategies for computer problem solving , 1984 .

[4]  H. V. Jagadish,et al.  Algorithms for Searching Massive Graphs , 1994, IEEE Trans. Knowl. Data Eng..

[5]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[6]  Joseph O'Rourke,et al.  Computational Geometry in C. , 1995 .

[7]  Joseph S. B. Mitchell,et al.  An Algorithmic Approach to Some Problems in Terrain Navigation , 1988, Artif. Intell..

[8]  Prof. Dr. Kikuo Fujimura Motion Planning in Dynamic Environments , 1991, Computer Science Workbench.

[9]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[10]  S. Tanimoto,et al.  Structured computer vision: Machine perception through hierarchical computation structures , 1980 .

[11]  James A. Storer,et al.  A single-exponential upper bound for finding shortest paths in three dimensions , 1994, JACM.

[12]  Kuo-Chin Fan,et al.  Solving Find Path Problem in Mapped Environments Using Modified A* Algorithm , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[13]  Charles H. C. Little,et al.  The Foundations of Topological Graph Theory , 1995 .

[14]  Ira Pohl,et al.  A book on C , 1984 .

[15]  Richard E. Korf,et al.  Linear-Space Best-First Search , 1993, Artif. Intell..

[16]  Longin Jan Latecki,et al.  Digitizations Preserving Topological and Differential Geometric Properties , 1995, Comput. Vis. Image Underst..

[17]  Ron Kimmel,et al.  Finding The Shortest Paths on Surfaces by Fast Global Approximation and Precise Local Refinement , 1996, Int. J. Pattern Recognit. Artif. Intell..

[18]  Giovanni Manzini,et al.  BIDA: An Improved Perimeter Search Algorithm , 1995, Artif. Intell..

[19]  James A. Storer,et al.  Shortest paths in the plane with polygonal obstacles , 1994, JACM.

[20]  Micha Sharir,et al.  A Survey of Motion Planning and Related Geometric Algorithms , 1988, Artificial Intelligence.

[21]  Peter C. Nelson,et al.  Perimeter Search , 1994, Artif. Intell..

[22]  Narendra Ahuja,et al.  Gross motion planning—a survey , 1992, CSUR.

[23]  Eric R. Zieyel Operations research : applications and algorithms , 1988 .