Mechatronics
I studied mechatronics during my MEng (Hons) in Design Engineering at the University of Bath - graduating in 2022. During this time I was part of a group project tasked with building a 'Mars Exploration’ rolling robot. The robot communicated with 'mission control' using a Raspberry Pi, with a camera ‘satellite’ tracking the robots location using ArUco codes and a Python image processing algorithm. It was necessary for the robot to perform in manual mode, automatically, and respond to a critical event.
Mars Exploration Rolling Robot
In a group project of four, I took Stateflow and Communications lead - integrating the mechanical and electrical systems to design control loops to control speed and position of the motors.
Test video of the rolling robot, where I was controlling its’ movements in manual mode.
Design Process
The image processing algorithm on the Raspberry Pi (RPi) would calculate the nearest path between AruCo code positions using satellite images as to output movement commands. I was responsible for designing the Finite State Machine (FSM) which takes the RPi output and drives the robot motors to reach the next code.
To reach this outcome, formative testing was done early and often in the design process. I had to pick up skills quickly and and learn through experimentation to become proficient in Python coding language and Simulink software. As a result, I developed motor and IMU control - thus improved the robots’ dynamics.
Creating a ‘manual mode’ controller at the start of the project allowed experimentation and learning to continue when progress relied on other team members’ work - improving overall time management and collaboration skills. The FSM created with Simulink also provided a user-friendly interface to integrate the mechanical and electrical components, therefore improved team collaboration by helping to visualise and prioritise the order of tasks.
Flowchart of the communication structure needed between mission control, the satellite, and the rolling robot for the robot to move as desired.
Design process to reach the final prototype.
The FSM for the rolling robot motor control. Note: the motors were mounted in opposite directions, hence opposing output signals would make the robot move forward or backwards.
Communication cycle of the IMU sensor used to maintain stability of the robot to allow its position to be tracked by clear imaging of its ArUco code. Accelerometer readings were used to measure and correct tilt when the robot was stationary.
Outcomes
Exploring and quickly prototyping concepts improved time-management, understanding of how systems integrate, and early identification of problems such as glare of the robots' plastic casing and the robots’ tilt preventing its position to be tracked. Learning quickly from prototyping was vital as the project was to be completed within a month, including the time for new course material to be taught.
The robot successfully communicated with mission control via Internet of Things technology. I became proficient with FSMs and Simulink software, whilst gaining knowledge of Python and electronic components.