Title
Stealth terrain navigation
Abstract
A method for solving visibility-based terrain path planning problems using massively parallel hypercube machines is proposed. A typical example is to find a path that is hidden from moving adversaries. This kind of problem can be generalized as a time-varying constrained path planning problem and is proven to be computationally hard. An approximation based on both temporal and, spatial sampling is proposed. Since a 2-D grid cell representation of terrain can be embedded into a hypercube with extra links for fast communication, the method can be very efficient when implemented on hypercube machines. The time complexity is in general O(T×E×log N) using O (N) processors, where T is the number of temporal samples, E is the number of adversary agents, and N is the number of grid cells on the terrain. It is also shown that the method can be applied to several realistic problems with a variety of path optimizations. All algorithms have been implemented on the Connection Machine CM-2 and results of experiments are presented
Year
DOI
Venue
1993
10.1109/21.214770
Systems, Man and Cybernetics, IEEE Transactions  
Keywords
Field
DocType
computational complexity,cooperative systems,hypercube networks,mobile robots,parallel machines,path planning,spatial reasoning,temporal reasoning,2D grid cell representation,Connection Machine CM-2,massively parallel hypercube machines,path optimizations,spatial sampling,stealth terrain navigation,temporal sampling,time complexity,time-varying constrained path planning problem,visibility-based terrain path planning problems
Motion planning,Binary logarithm,Spatial intelligence,Mathematical optimization,Computer science,Massively parallel,Terrain,Artificial intelligence,Time complexity,Machine learning,Hypercube,Computational complexity theory
Journal
Volume
Issue
ISSN
23
1
0018-9472
Citations 
PageRank 
References 
20
1.53
17
Authors
3
Name
Order
Citations
PageRank
Teng, Y.A.1201.53
Daniel Dementhon21327139.94
Larry S. Davis3142012690.83