This repo a ROS2 workspace. Each folder in src/ is a ROS2 package

• src/kalman_filter - Kalman Filter Localization
• src/planner - Motion planner and P-controller
• src/particle_filter - Particle Filter Localization

To setup the packages, build and source this workspace:

rosdep install --from-paths src --ignore-src -r -y
pip install scikit-image numpy matplotlib
colcon build --symlink-install
source install/setup.bash

Notes on ROS2

This kalman_filter package implements a linear Kalman Filter algorithm for estimating the pose of a 2D mobile robot. It uses IMU measurements as control inputs, and wheel encoders for sensor measurements.

See my whitepaper report for a complete explanation.

Click here for a Youtube video of the Kalman Filter in action!

In below image, the green path is ground truth, while red is the Kalamn Filter's estimate.

• ros2 launch kalman_filter kalman_filter.launch.py
• ros2 run turtlebot3_teleop teleop_keyboard (when not using a rosbag)
• In RViz, click on Publish Point to calculate MSE and view plots

A fairly linear path, provided by a precorded rosbag.

In below image, the green path is ground truth, while red is the Kalamn Filter's estimate.

See output folder for more plots and stats

Testing with a rather non-linear path. Evidently, a linear Kalman Filter is not suitable for such a path.

In below image, the green path is ground truth, while red is the Kalamn Filter's estimate.

See output folder for more plots and stats

• Turtlebot3 datasheet
• Kalman filter - Wikipedia
• kalmanfilter.net
• fjp - ROS Kalman Filter for Sensor Fusion
• fjp - Kalman Filter Math Explanation, Simple English
• ROS sensor fusion tutorial with Kalman Filter - Q Matrix

This tests out ROS2's Navigation Nav2 stack which generates a dynamic costmap, runs the AMCL node for localization, as well as some behavioural planners.

Click here for a demo video of the ROS2 navigation stack.

• ros2 launch turtlebot3_gazebo turtlebot3_house.launch.py
• ros2 launch turtlebot3_navigation2 navigation2.launch.py use_sim_time:=True map:=./src/planner/map/office_map/map.yaml
• Now use the 2D Pose Estimate and Nav2Goal functionality in RViz, and watch bevaviour of robot.

• nav_msgs/msg/OccupancyGrid.msg
• Published costmap topics
• Using RViz for ROS' Navigation stack
• ROS Map format
• Setting Up Lifecycle and Composition Nodes
• ROS2 Navigation stack intro:
  • ROS 2 Navigation
  • Navigating with a Physical Turtlebot 3
  • Getting Started

By Abhinav Agrahari, Ayush Ghosh, and Nick Shaju

Original repo

This planner package implements an A* Planner based on a given map, and a P-controller to autonomously guide the TurtleBot along the determined path.

Click here for a Youtube video of the path planner in action!

Pink/Purple/Blue is the inflated costmap. Green is the path the robot autonomously follows

• ros2 launch planner planner.launch.py
• For defining goals in RViz:
  • ros2 run planner navigation_client.py
  • Then in RViz, click Publish Point on the goal point
• For pre-defining a goal from terminal (modify x and y as needed):
  • ros2 run planner navigation_client.py --ros-args -p predefined_goal:=True -p goal_x:=4.0 -p goal_y:=0.8

The Nav2 package provides an inflated static costmap of the environment on the topic /global_costmap/costmap of type nav_msgs/msg/OccupancyGrid. We can use this in A* planning.

See Lab3_extra_notes for more

Drive around in the turtlebot3 house and visualize lidar scans:

Click here for a demo video

• ros2 launch turtlebot3_gazebo turtlebot3_house.launch.py
• ros2 run turtlebot3_teleop teleop_keyboard
• ros2 run rviz2 rviz2 -d rviz_configs/prelab3_LaserScan.rviz

By Abhinav Agrahari, Ayush Ghosh, and Nick Shaju

Original repo

This particle_filter package implements a Particle Filter for localizing a stationary 2D mobile robot using LiDAR data against a provided map, with a likelihood field model.

Click here for a Youtube video of the particle filter in action!

Yellow arrows are the Particles, while red is the super-imposed LiDAR data with the origin at average pose of the particle filter.

• ros2 launch particle_filter particle_filter_launch.py. If you get a Substituion Failure, make sure the exectuable listed in the error is marked as executable on your file system
• Wait for the launch file to finish loading. If the map does not appear, try re-running the launch file.
• ros2 bag play src/particle_filter/bag_files/point2 or ros2 bag play src/particle_filter/bag_files/point5