Autonomous Debris Detection & Removal Autonomous Robot — a purpose-built aquatic vehicle from Texas A&M University Corpus Christi that detects, navigates to, and removes surface debris without human intervention.
Robot Photo
About the Project
ADDRAR IV is the latest iteration of an autonomous surface vehicle (ASV) built by the Engineering Senior Design team at Texas A&M University Corpus Christi. The system uses a Raspberry Pi 5 and onboard camera to detect floating debris in real time using computer vision.
Once debris is located, the robot autonomously navigates to the target and activates its collection mechanism — removing trash from the waterway without human intervention during the mission.
Core Capabilities
A purpose-built marine platform combining autonomous navigation, debris detection, and collection into a single deployable unit.
Powered by a Raspberry Pi 5 and Pi Camera 3 Wide, the onboard AI vision system identifies floating debris in real time with a wide-angle field of view — distinguishing trash from natural objects on the water surface.
Integrated mesh netting between the twin catamaran hulls captures floating debris as the vessel moves forward, retaining collected material without requiring manual retrieval mid-mission.
Six waterproof ring motors with propellers provide omnidirectional thrust, enabling precise maneuvering in tight spaces like marinas, harbors, and coastal inlets.
Seamlessly switch between full AI autonomy and manual remote control, allowing operators to intervene for targeted collection or take over in complex scenarios.
Twin-hull design provides excellent stability in varying water conditions while creating a natural channel for debris to flow into the collection mesh.
All electronics are housed in sealed enclosures with protected ESC controllers, ensuring reliable operation in marine conditions with splash and spray protection.
AI Vision System
A trained computer vision model running on a Raspberry Pi 5 processes live video from the Pi Camera 3 Wide — detecting floating debris and autonomously steering the vessel toward it for collection.
The Pi Camera 3 Wide captures a continuous video stream with a 120° field of view, scanning the water surface ahead and to both sides of the vessel.
Each frame is fed into the Raspberry Pi 5 where the trained AI model runs inference in real time, analyzing every frame for debris objects against the water background.
The model draws bounding boxes around detected debris, classifying objects by type (plastic, wood, foam, mixed waste) and assigning a confidence score.
Detected debris coordinates are passed to the navigation system, which steers all six propellers to intercept and collect the target using proportional control.
The detection model was trained on a custom dataset of aquatic debris images captured in real coastal conditions around Corpus Christi.
IoT & Telemetry
ADDRAR streams real-time telemetry data from its onboard sensors via IoT, giving operators full visibility into the vessel's status, environment, and mission progress.
Real-time GPS coordinates streamed continuously, tracking ADDRAR's patrol route and current position.
Live voltage, current draw, motor RPM, and battery percentage — so operators know exactly when to recall the vessel.
All sensor data transmitted wirelessly to the cloud, enabling remote monitoring from any device through the dashboard.
Stream real-time video from the Pi Camera 3 Wide directly to the dashboard — first-person view with live debris detection overlay.
The live dashboard runs on the robot's Raspberry Pi. When the robot is powered on and connected, operators can stream video, view telemetry, and send commands.
Impact & Applications
Autonomous debris removal creates measurable impact across environmental, municipal, and maritime domains.
Continuous autonomous deployment removes plastic and waste before it sinks, breaks down, or harms marine life — operating in areas that are difficult or dangerous for human crews.
City stormwater systems and urban waterways accumulate debris rapidly after rain events. ADDRAR provides a cost-effective automated cleanup alternative to manual crew dispatch.
Harbors and marinas require constant debris management to protect vessel hulls, propellers, and infrastructure. ADDRAR handles routine surface debris autonomously.
Test Results
Results from controlled pool trials and coastal water testing sessions conducted by the TAMUCC team.
Media & Results
Photos, 3D design renders, engineering drawings, and test run results from the ADDRAR IV project.
Robot — Main View
3D Render — Top View
Water Test — Pool Trial
Engineering Drawing
3D Render — Exploded
Detection Accuracy Results
Technical Specifications
Full technical specs and bill of materials for ADDRAR IV.
| Platform | Catamaran ASV (twin-hull) |
| Compute | Raspberry Pi 5 |
| Camera | Raspberry Pi Camera 3 Wide — 12MP, 120° FOV |
| Propulsion | 6× waterproof ring motors w/ propellers |
| Motor Controller | Custom PWM / ESC system |
| Battery | LiPo pack (TBD mAh) |
| Est. Runtime | ~45 minutes (TBD) |
| Hull Material | ABS / PETG (3D printed) |
| IP Rating | IP65 splash proof |
| GPS | NEO-M8N (or equivalent) |
| Communication | Wi-Fi 802.11ac / Cloudflare Tunnel |
| AI Framework | OpenCV + YOLOv8 / ONNX |
| Dashboard | Flask + WebSocket (live) |
| Length | TBD cm |
| Width | TBD cm |
| Component | Description | Qty |
|---|---|---|
| RPi 5 | Main compute board | 1 |
| Pi Cam 3W | Wide-angle vision camera | 1 |
| Ring Motor | Waterproof brushless thruster | 6 |
| ESC | Electronic speed controller | 6 |
| LiPo Battery | Main power pack | 1 |
| GPS Module | NEO-M8N positioning | 1 |
| IMU | 6-DOF accel + gyro | 1 |
| Hull (printed) | ABS/PETG catamaran hulls | 2 |
| Mesh Net | Collection netting system | 1 |
| Voltage Reg. | 5V + 3.3V power distribution | 2 |
The Team
Senior design team at Texas A&M University Corpus Christi, College of Engineering & Computer Science.
Live System Access
Access the live control and monitoring interface. The dashboard runs on the robot's Raspberry Pi — only available when the robot is powered on and connected.
The robot streams live video, telemetry, and accepts remote commands via a Cloudflare Tunnel hosted on the onboard Raspberry Pi 5. When the robot is on, the dashboard is live at dashboard.addrarlivevideo.com.
If the Pi is powered off or disconnected, the dashboard will simply be unavailable — the info site remains online regardless.