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🏎️ Team 01

Autonomous
Racing

Pushing self-driving systems to their absolute limit — competing at the intersection of real-time perception, intelligent planning, and precise control.

Racing at the Edge of Autonomy

The Autonomous Racing team designs, builds, and competes with fully self-driving vehicles capable of navigating race circuits at high speed — without any human intervention during a race run.

Our system pipeline spans every layer of autonomous operation: LiDAR and camera-based environment mapping, real-time path planning via optimised trajectory algorithms, and low-latency control loops that keep the vehicle on the racing line at speed.

We compete in student autonomous racing competitions and continually benchmark our performance to close the gap to professional-grade systems. Whether it's cone detection on a closed circuit or dynamic obstacle avoidance, the challenge is always to go faster, more reliably.

ROS2 LiDAR Computer Vision SLAM Path Planning Embedded C++ Python

🎯 Perception

Multi-sensor fusion combining LiDAR point clouds and camera data to build a real-time map of the track, identifying cones, boundaries, and obstacles with high accuracy.

🧠 Planning

Onboard trajectory optimisation computes the ideal racing line in milliseconds, balancing speed against safety margins dynamically as conditions change.

⚡ Control

Low-latency PID and model-predictive control systems translate planned paths into precise throttle, brake, and steering commands at racing speeds.

🏁 Competition

We enter student autonomous motorsport competitions, measuring lap times and reliability as direct benchmarks for system performance improvements.

Racing Team
Members

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Team Lead
Team Captain

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Perception Engineer

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Path Planning

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Vehicle Control

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Software Engineer

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Hardware Engineer

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ML Specialist

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Systems Integration

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