Robotics, automation, MATLAB and practical coding
Selected work covering industrial automation support, COBOT and vision-system activity, MATLAB robotics simulation, and static website development.
Provided industrial automation support during my placement year at Caterpillar, covering COBOT and vision-system activity in a live manufacturing environment. The work focused on production support, fault investigation, validation activity and inspection reliability for automated systems.
Published details are limited to tools, techniques and transferable engineering work. Site-specific architecture, layouts, images, production data, equipment locations and internal documentation are excluded.
Work included support for automated inspection systems, COBOT-related production issues, fault investigation, issue logging, root-cause and corrective-action activity, and coordination with internal and external stakeholders.
The work sat at the interface between manufacturing engineering, automation, quality and technical support. The main objective was to improve confidence in automated systems while reducing avoidable production disruption.
No site-specific images, system architecture, layouts, line details, equipment locations, production rates or internal documents are published. Any future images will be self-made diagrams or public/licensed generic imagery only.
MATLAB implementation of a Rapidly-exploring Random Tree path-planning simulation using an office floor-plan environment. The project demonstrates map loading, obstacle representation, Dubins state-space planning, occupancy-map validation and path generation through a constrained workspace.
The simulation was developed in MATLAB using Robotics System Toolbox functions. Published evidence includes the generated figure and the visible source-code excerpt.
The script loads a predefined occupancy-map environment, applies obstacle data, defines a Dubins vehicle state space and uses an RRT planner to search for a route between the start and goal states. The resulting tree expansion and final path are plotted over the office floor plan.
The output figure shows the obstacle field, tree exploration and final planned path. The MATLAB source code is shown alongside the generated output.
clc;
clear all;
%% Section 1 - Laying out the floor plan
load exampleMaps.mat
whos *Map*
map = binaryOccupancyMap(complexMap, 2);
robotRadius = 0.2;
inflateRadius = 0.1;
mapInflated = copy(map);
inflate(mapInflated, inflateRadius);
% Adding obstacles
x = [12.0; 16.5; 10.0; 13.0; 23.0];
y = [8.0; 9.0; 5.0; 2.0; 12.0];
setOccupancy(map, [x y], ones(5, 1));
show(mapInflated)
%% Section 2 - StateSpaceDubins
stateSpace = stateSpaceDubins;
sv = validatorOccupancyMap(stateSpace);
sv.Map = map;
turningRadius = 0.1;
stateBounds = [0, 24; 0, 22; -pi, pi];
stateSpace.StateBounds = stateBounds;
%% Section 3 - RRT Programme
start = [2, 2, 0];
goal = [24, 15, 0];
planner = plannerRRT(stateSpace, sv, MaxConnectionDistance = 0.2);
rng(100, 'twister');
[pthObj, solnInfo] = plan(planner, start, goal);
show(map)
grid on;
title('Office Floor Plan')
hold on
plot(solnInfo.TreeData(:, 1), solnInfo.TreeData(:, 2), '.-')
plot(pthObj.States(:, 1), pthObj.States(:, 2), 'r-', 'LineWidth', 2)A vanilla JavaScript reimplementation of the same algorithm, running live in the browser with no dependencies. Click the canvas once to reposition the start marker, again to reposition the goal, then press Run. The tree expansion is deterministic for a given seed.
iterations 0 nodes 1 status: idle
This portfolio was built using HTML, CSS, and Javascript to present engineering evidence in a structured, maintainable and controlled format. The websites code, structure, and architecture may be viewed by pressing f12. To ensure all animations work on Windows OS, please go to Settings > Accessibility > Visual Effects > Toggle "Animation effects".
search-index.json and back.
Seven live pages (Home, About, Experience, CAD, Manufacturing, Robotics
& Automation, Dissertation), a shared stylesheet, and separate
images/, documents/ and videos/
trees organised by project. Every page uses the same header, navigation
and footer template for consistency.
Shared responsive navigation with hover dropdowns for the CAD, Manufacturing, and Robotics & Automation project groups. Layout uses CSS Grid and Flexbox for evidence grids, project cards, and the side-by-side figure/code display used on this page.
Media is organised per project (images, PDFs, and short MP4 loops for CAD demonstrations). Reports are linked directly as PDFs with visible preview images and captions. Alt text and figure captions are applied consistently for accessibility and clarity.
Industrial content is filtered before publication: no employee names, internal architecture, site-specific images, production rates, equipment locations or confidential drawings are shown. Approved screenshots and loops use visible captions and disclaimers.
The below dashboard is an example of consuming a third-party engineering API from the browser and rendering the response as an inline visualisation. The dynamic dashboard makes live requests to the UK National Grid ESO's public Carbon Intensity API on page load and refreshes every five minutes, showing the current grid carbon intensity, the last 24 hours as a sparkline, and the real-time generation mix by fuel type. It is written in vanilla JavaScript with no charting library, degrades gracefully when the API is unreachable, and demonstrates the same principles used when integrating SCADA, MES or IIoT feeds in a manufacturing setting.
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300
200
100
0
gCO₂/kWh
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|
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24h ago
12h ago
now
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| Time | |
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VERY LOW (<100)
LOW (100–199)
MODERATE (200–299)
HIGH ≥300 clips above chart
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/intensity/date returns the last 24 hours of
half-hourly readings for the sparkline, and /generation returns the current mix
by fuel type.