Title :
Numerical methods in search path planning
Author :
Yan, I. ; Blankenship, G.L.
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA
Abstract :
The detection search problem is the identification of search paths for a specified time interval [0,T], so that the expected number of surviving targets at time T is minimized. The problem can be solved in real time only when the two major procedures, namely estimation of target posterior distribution and evaluation of optimal controls (search path planning) based on this posterior target distribution, can be done online. The path-planning problem is difficult since the state space is infinite-dimensional. The authors introduce a discrete space-time model to which the ordered search algorithm in artificial intelligence graph search theory (with proper modification) can be applied. The algorithm not only stops at the (or an) optimal path but also expands far fewer nodes than an exhaustive search
Keywords :
artificial intelligence; graph theory; numerical methods; optimisation; artificial intelligence graph search theory; detection search problem; discrete space-time model; distribution estimation; infinite-dimensional state-space; minimization; numerical methods; optimal controls; ordered search algorithm; search path planning; target posterior distribution; Artificial intelligence; Differential equations; Educational institutions; Motion detection; Optimal control; Partial differential equations; Path planning; Probability density function; Search problems; State-space methods;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194592
