代写CE315 - Mobile Robotics Autumn 2025代写C/C++编程

Assignment - Simulated Robot Navigation

CE315 - Mobile Robotics

Autumn 2025

1 - Objectives

1.  To be familiar with Robot Operating System (ROS) and use it to do this assignment.

2.  To program a simulated robot to implement a specific navigation task below.

3.  To produce a report to explain your design, implementation, and results.

2 - Navigation task

2.1 - The Goal:

You should use the data collected in the environment shown in Figure 1, on Page 2 to control the robot moving from home, going through two gaps, and finally reaching to the charger. Also, you should collect odometry and laser data for creating trajectory, velocity, and map graphs for your Assignment report.

2.2 - The Software development:

Based on lab practices, you have gained knowledge on how to collect sensor data (Laser and Odometry) and how to control the robot motion.

You have been given most of software instructions in lab notes, which you should read care- fully and understand. Additionally, you have added new code during your lab practice.

Finally, you should be able to optimize your control code to make it concise.

You should run your control code in Gazebo simulator, and collect laser, odometry and velocity data for plotting graphs used in your report.

Figure 1: The Robot Navigation Path

3  - Deadline & submission requirements

The deadline for the electric submission of your report and C++ file (ce315_core_node.cpp) can be found on FASER. https://faser.essex.ac.uk

Your report should be 2000-3000 words long (no more than 25 pages).

1)  Cover Page (1 page):

Write your registration number (e.g.  1234567), the module code (CE315-6-AU), and a table of contents for easy navigation.

2)  Introduction (7 – 8 pages):

You should briefly describe a variety of elements you have learnt throughout this course. More specifically, describe and compare various:

→  Mobile robots - in terms of platforms and mobility.

→  Internal and external sensors.

→  Navigation approaches.

→  Path planning methods.

3)  Implementation of Odometry Control Strategy in Lab 3 (2 – 3 pages):

→  Present flowchartsto describe your code for the Lab 3 Odometry implementation. Your flowcharts should be clear and concise.

→  Display a graph showing the robot trajectory in X-Y coordinates and another graph showing the robot velocity in Velocity-Time coordinates using your Lab 3 code. Explain why they are in such shapes and how you selected the landmarks.

4)  Implementation of Laser Mapping in Lab 4 (1 – 2 pages):

→  Present flowchartsto describe your code for the Lab 4 Laser Mapping implement- ation. Your flowcharts should be clear and concise.

→  Display a graph showing the environment map detected by the LiDAR in X-Y co- ordinates. Explain why the graph has inaccuracies.

5)  Implementation of PID Control Strategy in Lab 5 (2 – 3 pages):

→  Present flowcharts to describe your code for the Lab 5 PID implementation. Your flowcharts should be clear and concise.

→  Display a graph showing both the robot trajectory and the environment map de- tected by the LiDAR in X-Y coordinates. Explain how you selected the desired val- ues for 3 of your PID controllers.

→  Display a graph showing the robot’s velocity in Velocity-Time coordinates and ex- plain why it is in such a shape.

6)  Map Improvement and Optimizing Your Code in Labs 6 - 8 (6 – 7 pages):

→  Revise the laser mapping code from Lab 4 to improve the quality of the laser map. Display a graph plotting the improved map. Explain your revised code.

→  Optimize your code used in the Lab 5 implementation.  Reduction in redundant code and better use of functions will reward more marks.

→  Include your optimized code (ce315_core_node.cpp) in the report, highlighting the sections you have optimized in yellow. Ensure that the code is fully functional before submission and explain the improvements you have made.

7)  Summary or Conclusion (0.5 page): You should make a summary or brief conclusion about your achievements.

4  - Assessment criteria

This assessment is based on the criteria below, accounted for 30% of total module credit.

→  The description and comparison quality of your introduction section (40%).

→  The implementation of the odometry control strategy and the quality of the graphs (15%).

→  The implementation of the PID control strategy and the quality of the graphs (15%).

→  The improvement of the environment map and the quality of your improved code (15%).

→  The writing quality of your report (5%) & the quality of your Lab 5 demonstration to GLAs (10%).