Today

Warm-Up Project Debrief
Conceptual introduction to the particle filter
We’re all living in a 1D world! (a simple particle filter example)

For Next Time

Complete this assignment on basic probability basic probability. Submit your work on canvas.
Read over the description of the Robot Localization project (there are a few modifications we still need to make, but nothing that will really impact an initial readthrough).
For more reinforcement of the concepts behind the particle filter, watch this video.

Warmup Project Debrief

Let’s go through the slide deck to share what you’ve done. Successes as well as hard-won lessons are equally welcome.

Conceptual Introduction to the Particle Filter

We’ll be doing an activity to introduce our next major topic in the class: robot localization. This is supposed to be a fun activity to get you thinking about the basic concepts.

We’re all living in a 1D world!

Before diving into this on your own, I want to show you some basic ideas in front of the class. The instructions for running thing are summarized below.

To get the code for today you will need to make sure your environment is setup with matplotlib and scipy. If you want to check you can use

$ pip3 show matplotlib scipy

If you get any warnings about package(s) not found, you can install them with pip3. For example, if I didn’t have either package, you can use the following command to install the necessary libraries.

$ pip3 install matplotlib scipy

Additionally, if you haven’t done so yet, clone the class activities are resources repo into your ros2_ws/src folder. If you’ve already cloned it, make sure to do a git pull origin main.

Next, make sure to build your workspace and source your install/setup.bash file.

$ cd ~/ros2_ws
$ colcon build --symlink-install
$ source install/setup.bash

To try things out, let’s first startup a 1d simulation of the world.

$ ros2 run simple_filter simple_filter_world.py --ros-args -p walls:=[0.0,3.0]

Take a look at the topics that are being published. What types of messages are there? What topics correspond to which messages? Take a moment with your partner and make a list of topics and what they might encode.

Next, we will experiment with our first particle filter:

$ ros2 run simple_filter simple_particle_filter.py --ros-args -p walls:=[0.0,3.0] -p nparticles:=100

A visualization should come up. The visualization shows the position of all the particles, the particle weights, and the true position. Additionally, a histogram is generated that shows the belief about where the robot is.

You can move your robot around using the following ROS node. To use this node make sure the window that pops up has focus, and use the a key and the d keys to move around left to right, respectively (sorry, I used to use the arrow keys, but I was finding that it didn’t work reliably,)

$ ros2 run simple_filter simple_controller.py

What happens over time to your visualization?

Try different wall configurations to see what happens. What happens as you change the number of particles? What happens if the wall configuration of the simulator and the particle filter model don’t match up?

Construct a scenario where there is an inherent ambiguity in determining where the robot is. How do you do this? What happens when you run your particle filter.

Team Formation

We’ll have some time for informal team formation at the end of class. Everyone must fill out this form to indicate your teammate, or if you don’t have one yet, you should provide me with some information to help match you.