%0 Journal Article
%T An improved particle filter for sparse environments
%A Prestes
%A Edson
%A Ritt
%A Marcus
%A F¨¹hr
%A Gustavo
%J Journal of the Brazilian Computer Society
%D 2009
%I Springer
%R 10.1007/BF03194506
%X in this paper, we combine a path planner based on boundary value problems (bvp) and monte carlo localization (mcl) to solve the wake-up robot problem in a sparse environment. this problem is difficult since large regions of sparse environments do not provide relevant information for the robot to recover its pose. we propose a novel method that distributes particle poses only in relevant parts of the environment and leads the robot along these regions using the numeric solution of a bvp. several experiments show that the improved method leads to a better initial particle distribution and a better convergence of the localization process.
%K boundary value problems
%K autonomous navigation
%K environment exploration
%K global localization
%K monte carlo localization.
%U http://www.scielo.br/scielo.php?script=sci_abstract&pid=S0104-65002009000300006&lng=en&nrm=iso&tlng=en