A heuristic search assisted active localization method is proposed. The algorithm clusters the particles by using adaptive particle clustering algorithm. Then, path planning trees and solution space trees are constructed respectively. Priories of all the nodes in the solution space trees are calculated according to the priority evaluation function, and the problem of path search is solved by the priority queue-type branch-and-bound method. Finally, a localizing accuracy active enhancing method is presented to solve the particle divergence problem in a single particle cluster. Simulation experiments validate the feasibility of the methods.
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