Hello! I am Dylan Black, a Fourth-year Bachelor of Mechanical and Mechatronic Engineering student at the University of Technology Sydney, with project experience in robotics, autonomous systems, computer vision, simulation, MATLAB signal analysis, and industrial engineering improvement experience.

I am interested in engineering roles involving robotics, space systems, simulation, software, automation, control systems, and applied problem solving.

Python-based drone simulation project integrating YOLO object detection with autonomous navigation and reinforcement learning control.

My contribution:

• Integrated YOLO-based object detection into the simulation environment.
• Worked on camera/image capture logic for detecting goal objects.
• Tested detection behaviour across different goal positions, camera settings, and confidence thresholds.
• Assisted with debugging the simulation and perception pipeline.

Technologies: Python, YOLO, PyBullet, OpenCV, reinforcement learning, simulation.

Robotics Studio project involving an autonomous fire-risk surveyor using UAV perception and UGV response coordination.

My contribution:

• Developed perception and object-mapping logic.
• Converted detected objects from sensor/camera data into global position estimates.
• Worked with ROS2 topics, transforms, and mapping outputs.

Technologies: ROS2, Python, computer vision, LiDAR/camera data, mapping, autonomous systems.

Dynamic systems project analysing phase response of a single-degree-of-freedom vibration rig using experimental oscilloscope data.

My contribution:

• Developed MATLAB scripts for FFT/FRF phase analysis.
• Implemented cross-correlation phase validation.
• Built theoretical SDOF phase response models.
• Compared experimental data against theoretical behaviour.

Technologies: MATLAB, FFT, FRF, cross-correlation, signal processing, dynamic systems.

Industrial robotics simulation involving Motoman GP7 integration, multi-robot kitchen automation, collision checking, E-stop logic, safety fencing, and a simulated light curtain.

My contribution:

• Created and integrated the Motoman GP7 robot model into the wider simulation.
• Developed GP7 pick-and-stir task logic using inverse kinematics, joint trajectories, and RMRC-style motion.
• Implemented safety-system logic including E-stop gating, reset/resume behaviour, and motion blocking.
• Built a simulated light curtain that detects robot links entering a protected zone.
• Added collision-checking and compact safety fence/barrier logic.

Technologies: Python, Robotics Toolbox, Swift, SpatialMath, DH modelling, inverse kinematics, collision checking, safety systems.

Programming: Python, MATLAB, C++, Git
Robotics & Simulation: ROS2, PyBullet, robot kinematics, autonomous systems
Computer Vision: YOLO, OpenCV, camera-based detection
Engineering Analysis: FFT, FRF, cross-correlation, data analysis, dynamic systems
Design & CAD: SolidWorks, CAD modelling, technical documentation
Professional Experience: Continuous improvement, process optimisation, SOP/PCI documentation, manufacturing support

LinkedIn: www.linkedin.com/in/dylan-black-17b0bb2ba Email: dylanjblack001@gmail.com