Statements (34)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Simultaneous Localization and Mapping algorithm
|
| gptkbp:advantage |
handles non-Gaussian noise
handles non-linearities |
| gptkbp:alsoKnownAs |
Monte Carlo Localization SLAM
|
| gptkbp:application |
autonomous vehicles
robotics |
| gptkbp:category |
gptkb:probabilistic_robotics
Bayesian filtering |
| gptkbp:citation |
OpenSLAM.org
|
| gptkbp:developedBy |
early 2000s
|
| https://www.w3.org/2000/01/rdf-schema#label |
Particle Filter SLAM
|
| gptkbp:input |
sensor data
odometry |
| gptkbp:limitation |
computationally expensive
particle depletion |
| gptkbp:notableContributor |
gptkb:Sebastian_Thrun
gptkb:Dieter_Fox gptkb:Wolfram_Burgard |
| gptkbp:output |
map of environment
robot pose estimate |
| gptkbp:referencePaper |
Probabilistic Robotics (Thrun, Burgard, Fox, 2005)
|
| gptkbp:relatedTo |
gptkb:FastSLAM
EKF SLAM |
| gptkbp:solvedBy |
localization problem
mapping problem |
| gptkbp:step |
prediction
resampling update |
| gptkbp:usedIn |
drones
mobile robots autonomous underwater vehicles |
| gptkbp:uses |
particle filter
|
| gptkbp:bfsParent |
gptkb:Extended_Kalman_Filter_Simultaneous_Localization_and_Mapping
|
| gptkbp:bfsLayer |
8
|