Cosi119a

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## Navigation

* Continuing from where we left off
* We have created a map using slam
* How do we use it for navigation?

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### SLAM

* Simultaneous Localization and Mapping
* We wil`l localize the robot on a map that is incomplete
* When it leaves the map it is able to extend it with the same algorithm

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### Reconstruct where we left off

<div class="callout callout-small">
  <span class="callout-badge">NB</span> Be careful with the filenames of the map. You will get strange errors if the file name given to turtlebot3_navigation is incorrect or not resolvable!
</div>

<pre><code class="language-bash">
# create the simulated environment called stage_4
$ roslaunch turtlebot3_gazebo turtlebot3_stage_4.launch

# launch a simulated turtlebot3 that drives a random pattern
$ roslaunch turtlebot3_gazebo turtlebot3_simulation.launch

# launch the slam algoritm, which will create an in-memory map data structure
$ roslaunch turtlebot3_slam turtlebot3_slam.launch slam_methods:=gmapping

# After the map looks done, save it into a map file for later.
$ cd ~
$ rosrun map_server map_saver -f stage4
</code></pre>

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### Navigating

<pre><code class="language-bash">
# Now, close all the exiting ROS nodes down and next run this. Be careful with the
# file names because the yaml file contains a file name too and it is easy to 
# get things misaligned. 
# {filemname} will be something like /home/youraccount/stage4.yaml but check to make sure.

$ roslaunch turtlebot3_gazebo turtlebot3_stage_4.launch
$ roslaunch turtlebot3_navigation turtlebot3_navigation.launch map_file:={filename}
</code></pre>

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### Navigate

* Give the robot an estimated position
* Give the robot a navigation goal by clicking the button in rviz
* Play around and see the robot solve the simple maze navigation including places it can't 'see' from where it is

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### Explanation

* The ROS **nav stack** is another complex bit of computer science, mathematics, and engineering
* For now we are going to just scratch the surface
* Inputs are a map, an estimated current position, scanner information, and a destination
* Behavior is to generate a path and steer the robot to it
* Avoiding obstacles

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### How it works
1. *navigation goal* is sent to the **nav stack**. This is done with an action call with a goal of *MoveBaseGoal* which specifies a target pose and a coordinate frame (called the *map* frame.)
1. Nav stack uses a path-planning algorithm in the *global planner* to create shortest path route
1. Local planner drives along that path, while using sensor information to aboid obstacles.
1. When the robot arrives at the goal pose the action terminates.

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### AMCL

* Uncheck everything except RobotModel, Map and ParticleCloud in rViz.
* The green arrows are the pose estimates from `amcl`
* Tell `amcl` that the robot is somewhere else, and you see it do its best on guessing the pose
* Do this with the *2d pose estimate* command
* Turn on the Laser Scan display
* Play with the *2d pose estimate* command and observe how the map becomes aligned
* Also with `/initialpose` topic (which is how, perhaps, we tell AMCL about a fiducial that has been identified.)