Intervisibility heuristics for computer generated forces

Rajput, Sumeet; Karr, C. R.; Petty, Mikel D.; Craft, Michael A.

doi:10.1117/12.204226

Cited by 2 publications

(2 citation statements)

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Section: Disadvantagesmentioning

confidence: 99%

“…geometric path planning algorithms [15] or its variants [12,13,18,26,31,32]. For example, A £ has been used in a number of computer generated forces systems as the basis of their planning component, to plan road routes [3], avoid moving obstacles [10], avoid static obstacles [18] and to plan concealed routes [14]. Very extensive discussion related to geometric shortest path planning algorithms was presented by Mitchell in [15] (references consist of 393 papers and handbooks).…”

Section: Disadvantagesmentioning

confidence: 99%

See 1 more Smart Citation

Military route planning in battlefield simulation: effectiveness problems and potential solutions

Tarapata

2003

JTIT

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Path searching is challenging problem in many domains such as simulation war games, robotics, military mission planning, computer generated forces (CGF), etc. Effectiveness problems in military route planning are related both with terrain modelling and path planning algorithms. These problems may be considered from the point of view of many criterions. It seems that two criterions are the most important: quality of terrain reflection in the terrain model and computational complexity of the on(off)-line path planning algorithm. The paper deals with two above indicated problems of route planning effectiveness. Comparison of approaches used in route planning is presented. The hybrid, terrain merging-based and partial path planning, approach for route planning in dynamically changed environment during simulation is described. It significantly increase effectiveness of route planning process. The computational complexity of the method is given and some discussion for using the method in the battlefield simulation is conducted. In order to estimate how many times faster we can compute problem for finding shortest path in network with n big squares (b-nodes) with relation to problem for finding shortest path in the network with V small squares (s-nodes) acceleration function is defined and optimized.

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