Contents
What is grid based SLAM?
▪ SLAM stands for simultaneous localization and. mapping. ▪ The task of building a map while estimating. the pose of the robot relative to this map.
How does FastSLAM work?
FastSLAM is a SLAM algorithm that integrates particle filters [18, 37] and extended Kalman filters. FastSLAM estimates these feature locations by EKFs. The basic algorithm can be implemented in time logarithmic in the number of landmarks, using efficient tree representations of the map [45].
How does a particle filter work?
Particle filtering uses a set of particles (also called samples) to represent the posterior distribution of some stochastic process given noisy and/or partial observations. In the resampling step, the particles with negligible weights are replaced by new particles in the proximity of the particles with higher weights.
Is it easy to use grid based SLAM?
Grid-based SLAM As with landmarks, the map depends on the poses of the robot during data acquisition ! If the poses are known, grid-based mapping is easy (“mapping with known poses”) 8
How to build robot mapping grid based FastSLAM?
Robot Mapping Grid-based FastSLAM Cyrill Stachniss 2 Motivation So far, we addressed landmark-based SLAM (EKF, SEIF, FastSLAM) ! We learned how to build grid maps assuming “known poses” Today: SLAM for building grid maps 3 Mapping With Raw Odometry Courtesy: Dirk Hähnel 4 Observation Assuming known poses fails! Questions
How is the SLAM algorithm used in robotics?
The SLAM algorithm combines localization and mapping, where a robot has access only to its own movement and sensory data. The robot must build a map while simultaneously localizing itself relative to the map. The map and the robot pose will be uncertain, and the errors in the robot’s pose estimate and map will be correlated.
How is the particle filter used in Slam?
It is used with feature-based maps (see gif above) or with occupancy grid maps. As it is shown, the particle filter differs from EKF by representing the robot’s estimation through a set of particles.