Fix typos discovered by codespell (#1684)

Signed-off-by: Christian Clauss <cclauss@me.com>
master
Christian Clauss 2022-09-13 14:34:12 +02:00 committed by GitHub
parent 062513df85
commit a727ea8f6c
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4 changed files with 5 additions and 5 deletions

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@ -146,7 +146,7 @@ AssetsWriter::AssetsWriter(const std::string& pose_graph_filename,
<< "Pose graphs contains " << pose_graph_.trajectory_size()
<< " trajectories while " << bag_filenames_.size()
<< " bags were provided. This tool requires one bag for each "
"trajectory in the same order as the correponding trajectories in the "
"trajectory in the same order as the corresponding trajectories in the "
"pose graph proto.";
// This vector must outlive the pipeline.

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@ -253,7 +253,7 @@ Scan matching starts by aligning far points of the low resolution point cloud wi
Global SLAM
-----------
While the local SLAM generates its succession of submaps, a global optimization (usually refered to as "*the optimization problem*" or "*sparse pose adjustment*") task runs in background.
While the local SLAM generates its succession of submaps, a global optimization (usually referred to as "*the optimization problem*" or "*sparse pose adjustment*") task runs in background.
Its role is to re-arrange submaps between each other so that they form a coherent global map.
For instance, this optimization is in charge of altering the currently built trajectory to properly align submaps with regards to loop closures.
@ -269,7 +269,7 @@ The optimization is run in batches once a certain number of trajectory nodes was
The global SLAM is a kind of "*GraphSLAM*", it is essentially a pose graph optimization which works by building **constraints** between **nodes** and submaps and then optimizing the resulting constraints graph.
Constraints can intuitively be thought of as little ropes tying all nodes together.
The sparse pose adjustement fastens those ropes altogether.
The sparse pose adjustment fastens those ropes altogether.
The resulting net is called the "*pose graph*".
.. note::

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@ -69,7 +69,7 @@ use_nav_sat
use_landmarks
If enabled, subscribes to `cartographer_ros_msgs/LandmarkList`_ on the topic
"landmarks". Landmarks must be provided, as `cartographer_ros_msgs/LandmarkEntry`_ within `cartographer_ros_msgs/LandmarkList`_. If `cartographer_ros_msgs/LandmarkEntry`_ data is provided the information
will be included in the SLAM accoding to the ID of the `cartographer_ros_msgs/LandmarkEntry`_. The `cartographer_ros_msgs/LandmarkList`_ should be provided at a sample rate comparable to the other sensors. The list can be empty but has to be provided because Cartographer strictly time orders sensor data in order to make the landmarks deterministic. However it is possible to set the trajectory builder option "collate_landmarks" to false and allow for a non-deterministic but also non-blocking approach.
will be included in the SLAM according to the ID of the `cartographer_ros_msgs/LandmarkEntry`_. The `cartographer_ros_msgs/LandmarkList`_ should be provided at a sample rate comparable to the other sensors. The list can be empty but has to be provided because Cartographer strictly time orders sensor data in order to make the landmarks deterministic. However it is possible to set the trajectory builder option "collate_landmarks" to false and allow for a non-deterministic but also non-blocking approach.
num_laser_scans
Number of laser scan topics to subscribe to. Subscribes to

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@ -66,7 +66,7 @@ You can then use Cartographer as part of your calibration process to improve the
Multi-trajectories SLAM
=======================
Cartographer can perform SLAM from multiple robots emiting data in parallel.
Cartographer can perform SLAM from multiple robots emitting data in parallel.
The global SLAM is able to detect shared paths and will merge the maps built by the different robots as soon as it becomes possible.
This is achieved through the usage of two ROS services ``start_trajectory`` and ``finish_trajectory``. (refer to the ROS API reference documentation for more details on their usage)