Simultaneous localization and mapping (SLAM) is a method to help robots explore, navigate, and map an unknown environment. It is well known that traditional methods for SLAM based on the extended Kalman filter (EKF) suffer computational complexity problems when dealing with large scale environments, as well as inconsistencies for non-linear SLAM problems.
Showing posts with label close loop. Show all posts
Showing posts with label close loop. Show all posts
Saturday, December 18, 2010
Slam Music Tour Dates: Eureka moments! Slam Implementation using ESDF
Labels:
bearin,
camera views,
close loop,
complexity problems,
computational complexity,
correlative,
extended kalman filter,
information matrix,
linear measurements,
loop closures,
newell simon hall,
open loop,
pseudo code,
rigid body,
rms titanic,
scale environments,
sparsity,
team mate
Eureka moments! Slam Implementation using ESDF
Simultaneous localization and mapping (SLAM) is a method to help robots explore, navigate, and map an alien environment. It is easily known that traditional methods for SLAM based on the extended Kalman filter (EKF) suffer computational complexity problems when dealing with large scale environments, as good as inconsistencies for non-linear SLAM problems.
Labels:
bearin,
camera views,
close loop,
complexity problems,
computational complexity,
correlative,
extended kalman filter,
information matrix,
linear measurements,
loop closures,
newell simon hall,
open loop,
pseudo code,
rigid body,
rms titanic,
scale environments,
sparsity,
team mate
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