Project 4 - JetAuto Mapping
Due: Sunday, Mar 29, 2026 at 11:59 PM on Blackboard
Weight: 20%
Introduction
In this project, you will learn the fundamentals of environment mapping for autonomous robots. You will manually operate the robot to map a designated indoor area using ROS mapping packages (SLAM-based tools). The robot will collect LiDAR sensor data while moving through the environment and generate a map of the area. You will then save the generated map and analyze it to ensure that it accurately resembles the area used for mapping.
Objectives
- Understand the concept of mapping in autonomous robots.
- Learn how Simultaneous Localization and Mapping (SLAM) systems build maps of unknown environments.
- Generate an accurate map of a designated environment.
- Save the generated map for later use.
- Interpret occupancy grid maps and understand how robots represent environments.
- Answer the assessment questions.
NOTE: This project must be completed individually.
Step 1: Set up the robot and launch the SLAM mapping service
- In groups of up to 3 students, set up the JetAuto robot.
- Follow the instructions from Lab 6 to start the SLAM mapping service.
Step 2: Teleoperate the JetAuto robot for mapping
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Follow the instructions from Lab 6 to teleoperate the robot through a designated area for mapping (assigned Zone by the instructor).

Figure P4.1 Hallway Mapping Zone (Ignore the purple dot and the diagonal line)
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Ensure the robot covers the entire environment to create a complete map.
- Monitor the mapping process using RViz.
- Save the final map once mapping is complete.
Step 3: Analyze the map
- Take a screenshot of the generated maps and analyze their quality and identify any potential errors.
Assessment Questions
- What is the purpose of mapping in autonomous robots?
- What type of map representation is commonly used in ROS mapping systems?
- How does RViz help during the mapping process?
- What factors can affect the accuracy of the generated map? How do a chair, table, door, and window look in the map?
- Explain the role of robot sensors in building the map.
- What files are generated when saving a map, and what is the purpose of each file? (Check the directory manually!)
Submission
- The saved map files (map.pgm and map.yaml) from the classroom and from the assigned Zone.
- A screenshot of the map files identifying any potential errors. A low-quality map with a lot of non-continuous boundaries and missing features will result in a grade reduction.
- A short video showing the mapping process in RViz using the real robot (not from a Gazebo simulation).
- A text file containing the answers to the questions (one per group).
Late Submission Penalty
- A 25% reduction from the full mark will be applied for every 24 hours the submission is late after the deadline.