DTU AUV Fleet

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Autonomous Underwater Vehicles — Engineered at DTU

ARKAJA 2.0
Autonomous Underwater Vehicle

ARKAJA 2.0

Designed and built by the DTU AUV team for underwater exploration, autonomous navigation, and robotics competition.

NATIONAL EVENTRYIC 2026

SEWA - ROVC Challenge 2026

Design, build, and operate a Remotely Operated Underwater Vehicle for real-world subsea missions at Delhi Technological University.

Students building and celebrating with a tethered ROV
Venue DTU Swimming Pool Complex, New Delhi

The Deep-Water Robotics Arena

Teams bring a tethered ROV of their own design to a controlled pool course and run it through three missions: piloting, vision and navigation.

  1. 01

    Gate Navigation

    Pilot through submerged hoops while holding depth against current.

  2. 02

    Target Identification

    Find and track underwater markers on camera in murky water.

  3. 03

    Maze Traversal

    Work a path through the pool maze using acoustic and visual cues.

1st place
₹2.5 L
2nd place
₹1.5 L
3rd place
₹1.0 L
Register by
10 Sep
Team size
5 + 1 mentor
School & college
01OUR APPROACH

Engineering Philosophy

Every vehicle we build reflects our core principles — iterative design, rigorous testing, and relentless innovation.

Research-First Design

Every component decision is backed by research papers, CFD simulations, and prototyping. We don't guess — we validate.

Iterative Development

Each generation builds on lessons from the last. Failures become blueprints for breakthroughs.

Modular Architecture

Swappable subsystems mean faster debugging, easier upgrades, and parallel development across teams.

Test-Driven Integration

Pool tests, pressure tests, and simulation — every system is proven before it goes underwater.

02TECHNOLOGY

Core Technologies

The tools, frameworks, and hardware powering our autonomous vehicles.

ROS 2

Robotics middleware for autonomous control, sensor fusion, and inter-process communication.

OpenCV + YOLO

Real-time underwater object detection and visual servoing for task execution.

Jetson + STM32

NVIDIA Jetson for AI inference paired with STM32 microcontrollers for low-level motor & sensor control.

SolidWorks

CAD modeling and FEA simulations for hull design, thruster mounts, and watertight enclosures.

KiCad

Custom PCB design for power distribution boards, motor drivers, and sensor interface circuits.

Acoustics

Hydrophone arrays and DSP algorithms for underwater acoustic localization and pinger detection.