Name: Purple Pink Gradient Modern Metaverse Presentation
Uploaded: 2025-09-15
Duration: 4 min 49 s
Description: Hello everyone, we are Team InnoVortex from the Department of Computer Science and Engineering, Manakula Vinayagar Institute of Technology, Puducherry..

[Audio] Hello everyone, we are Team InnoVortex from the Department of Computer Science and Engineering, Manakula Vinayagar Institute of Technology, Puducherry.. 

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[image] A black and white logo AI generated content may be incorrect

InnoVortex Cleaner – Smart Robotic Vacuum Cleaner

[Audio] Our team members are Rooban, Suriya, Arul, Guru Prasanth, and Sabarinathan, and we are mentored by Mrs. G. Sharmila.
We proudly present our project – the InnoVortex Cleaner: A Smart Robotic Vacuum Cleaner designed for AtomQuest 2025.. 

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Department of Computer Science and Engineering

A blue and yellow sign with white text

AI-generated content may be incorrect.

A person in a suit and tie

AI-generated content may be incorrect.

[Audio] Existing robotic cleaners face three major limitations:
Poor efficiency in corner cleaning,
Tangling issues with hair and wires, and
Difficulty in adapting to random obstacles.. 

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Cleaning bots often fail in corner cleaning, tangled debris (hair, wires) and random obstacle navigation.
 The competition requires a bot that:
 Works on smooth flat office-like floors.
 Handles dust, paper, hair, wrappers (<30×30 mm).
 Adapts to randomly placed obstacles.
 The bot that cleans the maximum waste efficiently wins.

[Audio] Key components include Raspberry Pi 5, LiDAR. 

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InnoVortex Cleaner: Smart, Efficient, Versatile

AI-driven debris detection – identifies type of waste.
 Vortex-enhanced suction – fine dust & hair.
 Tangle-free brushes – wires & strands.
 LiDAR-based SLAM navigation – adapts to obstacles, ensures >90% coverage.

[Audio] To build our prototype, we have procured:
Raspberry Pi 5 for AI and SLAM processing,
Ultrasonic sensors for 360-degree obstacle detection,. 

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Raspberry Pi 5 (Controller): High-performance processing for AI models, SLAM, and real-time decision-making.
 Ultrasonic Sensors (Obstacle detection): Provide 360° awareness of close-range obstacles to avoid collisions.
 LiDAR (Mapping & navigation): Enables SLAM for accurate mapping and efficient coverage in random layouts.
 ESP32-CAM (Debris classification): Identifies dust, hair, and wrappers for adaptive cleaning.
 DC Motors + L298N Driver: Ensure smooth movement and precise control of the bot’s wheels.

[Audio] ultrasonic sensors, ESP32-CAM, DC motors with drivers. 

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Vortex Blower Fan (Suction): Creates powerful airflow to capture fine dust and hair effectively.
 Brushes (Side + Roller): Sweep debris from edges and prevent tangling of hair/wires.
 12V Li-ion Battery (6000mAh): Provides 60–75 mins runtime, supporting extended cleaning sessions.
 Dust Bin (600ml with HEPA filter): Captures debris and prevents dust leakage for cleaner air.
 3D-Printed Chassis (PLA/ABS blend): Lightweight, durable body for housing electronics and mechanisms.

[Audio] vortex blower fan, brushes, 12V Li-ion battery,. 

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A person holding up a piece of paper

AI-generated content may be incorrect.

A person in a suit sitting at a table with several small blue and white objects

A person in a suit and tie sitting at a table with a small blue light

AI-generated content may be incorrect.

A person holding a bag of food

AI-generated content may be incorrect.

[Audio] HEPA dust bin, and a 3D-printed chassis.". 

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[Audio] We're finalizing vortex chamber tuning, custom PCB fabrication, and final chassis wiring.. 

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Vortex Suction Chamber Tuning: Custom 3D-printed airflow design; current prototype requires optimization for maximum suction efficiency.
 Mini Robotic Arm Final Assembly: Servo-based arm for wrappers is under calibration; parts ordered and awaiting fitting.
 Custom PCB Integration: Circuit design completed; fabrication delayed due to supplier lead time.
 Final Chassis Fitting & Wiring: Dependent on completion of PCB and robotic arm; scheduled after pending components arrive.

[Audio] "Next, we'll integrate components, train AI models, test navigation, and optimize suction and brush speed for maximum dust collection.". 

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Combine sensors, suction and controller into a single working prototype.

Improve debris detection accuracy using custom  datasets for dust and hair.

Validate obstacle avoidance  and SLAM mapping in simulated challenge-room conditions.

Fine-tune suction airflow, battery efficiency and brush speed for maximum dust collection.

Demonstrate a fully functional prototype with motion, dust cleaning and extra features.

[Audio] "Compared to existing bots, ours excels in multi-debris handling, obstacle navigation, and cleaning efficiency while staying cost-effective.". 

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[image] Performance Analysis
i ation Autonomy (%)
Obstacle Avoi
Suction Pow
InnoVortex Cleaner
Dreame X40 Ultra
iRobot Roomba j9+
1
450
ion Capacity (g)
300
s
60
40
20
D
1100
ffectiveness (USD)

[Audio] "Our four-layer system: • Perception – sensors collect data • Processing – Pi 5 runs AI and SLAM • Decision – selects actions • Actuation – motors, brushes, and suction execute cleaning.". 

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[image] Motors Block
Dust Bin
Power Supply:
12V 6000mAh Battery
r 98
Microcontroller: Raspberry Pi 5
A1 Processin Block
A1 Mapping & Debri
Detection (SLAM)
avigation & Cleaning
Logic (DWA)
Navigation Block
Dust Sensor
(GP2Y1010AUOF)
Oust Sensor
TF-Luna LiDAR
module
Sensors
ESP32-CAM module
MPU6050 IMU
sensor
•iuccXi
SCLO-•
•son
III
Ultrasonic Sensor
(HC-SR04)

[Audio] "Our NavigateAndClean algorithm maps the room, classifies debris, activates suction or brushes, and plans paths with DWA until cleaning is complete. 

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Algorithm: NavigateAndClean()     Input: SensorData (LiDAR, Camera, Dust), RoomMap     Output: CleanedArea, DustCollected     Begin         Initialize SLAM(RoomMap)         While (Not Full(Bin))             DebrisType = ClassifyDebris(CameraData)             If (DebrisType == "Fine Dust")                 ActivateVortexSuction()             Else If (DebrisType == "Hair" OR     "Wrapper")                 ActivateBrushes()                 If (DebrisType == "Wrapper")                     ActivateArm()                 End If             End If             Path = DWA(SensorData, RoomMap)             Move(Path)             DustCollected += MeasureDust(DustSensor)             UpdateMap(RoomMap)         End While         Return CleanedArea, DustCollected     End

Start
tialize Sensors
C-arnera. Dust •
Detect Debris Typ
r, A1 Classification
Fille DX1st
Activate V o rtex
S u eti o n
Activate Brushes
Rob o tic Arm-n
Store in Bin
Bin Full
E nupty B in
End

[Audio] "We confirm that our mentor Mrs. G. Sharmila has approved and guided our work.". 

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[Audio] "InnoVortex Cleaner combines AI, suction, and smart navigation to tackle real cleaning challenges. Future plans include a mini robotic arm, wet mopping, mobile app control, and auto-charging. Thank you!". 

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We bring intelligence, efficiency and versatility into cleaning.






  With innovation and teamwork, we’re ready to clean the competition!

Purple Pink Gradient Modern Metaverse Presentation

Hello everyone, we are Team InnoVortex from the Department of Computer Science and Engineering, Manakula Vinayagar Institute of Technology, Puducherry.

avatar

Our team members are Rooban, Suriya, Arul, Guru Prasanth, and Sabarinathan, and we are mentored by Mrs  G Sharmila.
We proudly present our project – the InnoVortex Cleaner: A Smart Robotic Vacuum Cleaner designed for AtomQuest 2025.

Existing robotic cleaners face three major limitations:
Poor efficiency in corner cleaning,
Tangling issues with hair and wires, and
Difficulty in adapting to random obstacles.

Key components include Raspberry Pi 5, LiDAR

To build our prototype, we have procured:
Raspberry Pi 5 for A-I  and S-L-A-M processing,
Ultrasonic sensors for 360-degree obstacle detection,

ultrasonic sensors, ESP32-CAM, DC motors with drivers

vortex blower fan, brushes, 12 volts Li ion battery,

H-E-P-A dust bin, and a 3D-printed chassis."

We're finalizing vortex chamber tuning, custom P-C-B fabrication, and final chassis wiring.

"Next, we'll integrate components, train A-I  models, test navigation, and optimize suction and brush speed for maximum dust collection."

"Compared to existing bots, ours excels in multi debris handling, obstacle navigation, and cleaning efficiency while staying cost effective."

"Our four layer system: 
 Perception – sensors collect data 
 Processing – Pi 5 runs A-I  and S-L-A-M 
 Decision – selects actions 
 Actuation – motors, brushes, and suction execute cleaning."

"Our NavigateAndClean algorithm maps the room, classifies debris, activates suction or brushes, and plans paths with D-W-A until cleaning is complete

"We confirm that our mentor Mrs  G Sharmila has approved and guided our work."

"InnoVortex Cleaner combines A-I , suction, and smart navigation to tackle real cleaning challenges. Future plans include a mini robotic arm, wet mopping, mobile app control, and auto charging. Thank you!"

Purple Pink Gradient Modern Metaverse Presentation

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