OPEN-SOURCE & HARDWARE REPOSITORIES

ENGINEERING ARCHIVES

Autonomous Mobile Robots, Sim-to-Real Digital Twins, and Embedded Hardware Systems

ROBOTICS & HARDWAREAug 2026

Hybrid Vortex Crawler: Multi-Surface Wall-Climbing Robot

Multi-Surface Vertical Scaling & NDE Payload Delivery (NeX-Gen Robotics Challenge 2026 | IDREA)

Holding Downforce45 N (EDF Vortex)
Payload Capacity1.5 kg (NDE Probes)
Control Dual-TierROS 2 / FreeRTOS
Motor PWM Frequency20 kHz

Engineered an industrial wall-climbing inspection robot utilizing an active aerodynamic vortex 70mm Electric Ducted Fan (EDF) generating 45 N holding force combined with passive N52 magnetic track locking. Implemented a dual-tier control hierarchy: ROS 2 Jazzy on Raspberry Pi 4 for high-level mission logic and ToF telemetry, paired via UART to an ESP32 FreeRTOS controller for deterministic motor actuation and 50Hz tilt stabilization.

TECHNICAL ACHIEVEMENTS:
  • Designed in Autodesk Fusion with 3mm CNC carbon fiber plates, Pololu 30T rubber tracks, and 4x 164 RPM planetary gear motors.
  • Delivers 1.5 kg payload capacity for Non-Destructive Evaluation (NDE) ultrasound probes and HD thermal inspection.
  • Dual-tier control: ROS 2 Jazzy mission supervisor (RPi4) coupled with FreeRTOS 20 kHz deterministic motor PWM (ESP32).
  • Qualified for NeX-Gen Robotics Challenge 2026 (IDREA | Round 1 Concept Presentation).
ROS 2 JazzyRaspberry Pi 4ESP32 (FreeRTOS)Dual BTS7960 H-Bridges70mm EDFMPU6050 IMUFusion 360Three.js
PHYSICAL AI & DIGITAL TWINAug 2026

AutoTwin-AI: Sim-to-Real Digital Twin

Zero-Defect Anomaly Detection in Automotive & Industrial Discrete Manufacturing

Defect Photos Needed0 (CAD Only)
Synthetic Renders4,851
Edge Latency<42 ms
Convergence Loss (MSE)0.000092

Proprietary Sim-to-Real Digital Twin pipeline eliminating the physical defect collection bottleneck. Ingests native 3D CAD files, generates 4,851 ray-traced domain-randomized synthetic renders under extreme illumination/camera noise, and trains an unsupervised PyTorch Autoencoder to localize micro-anomalies in sub-millimeter precision via reconstruction residual errors (L = ||X - X̂||²).

TECHNICAL ACHIEVEMENTS:
  • Trained across 50 epochs on NVIDIA RTX 3050 Laptop GPU in ~128.8 min with MSE loss reaching 0.000092.
  • Engineered FastAPI / TensorRT edge inference node delivering frame evaluation under 42ms.
  • Constructed a 3-panel WebGL dashboard (Live Camera, AI Reconstruction, Residual Heatmap) for instant PLC line-trip alerts.
PyTorchConvolutional Autoencoder (CAE)Blender OptiXFastAPITensorRTThree.jsWebGLDocker
ROBOTICSJul 2026

OOMWOO: Autonomous Robot Vacuum System

Authored core open-source coverage planning modules for the OOMWOO autonomous vacuum robot (oomwoo_clean_and_map). Implemented Boustrophedon Cellular Decomposition (BCD) for complete workspace coverage and integrated SLAM Toolbox for online map generation and localization under ROS 2 Jazzy.

ROS 2 (Jazzy)Nav2SLAM ToolboxPython
AI-VISIONNov 2025

Smart Traffic Management System (SIH25050)

Built a vision-based adaptive traffic signal controller utilizing YOLO object detection to dynamically calculate vehicular queue density across multi-lane intersections and modulate green-light intervals.

PythonYOLOv8OpenCVFastAPI
FULLSTACKFeb 2026

Hybrid AI Scholarship Policy Engine

Engineered an anomaly detection and policy verification bot designed to automate scholarship eligibility parsing, document fraud detection, and compliance auditing with an interactive Streamlit UI.

PythonScikit-LearnStreamlitOCR
SCHOLARLY PREPRINTS

RESEARCH & PUBLICATIONS

Indexed Preprints, DOI Registrations & Multi-Agent RL Formulations

PUBLISHED PREPRINTAugust 2026

Sensor-Fusion Driven Deep Reinforcement Learning for Dynamic Traffic Signal Optimization

Author: Deepak RZenodo Preprint

DOI: 10.5281/zenodo.20265628

This paper presents a closed-loop, decentralized urban traffic management architecture integrating real-time computer vision telemetry with multi-agent reinforcement learning (MARL). By ingesting optical density metrics and vehicle queue trajectories, the policy dynamically adjusts signal timing to maximize arterial throughput while minimizing waiting variance.

KEY CONTRIBUTIONS:
  • Closed-loop telemetry pipeline fusing edge vision detections directly into policy state space.
  • Multi-agent reward formulation preventing congestion spillover across adjacent intersections.
  • Open access publication and dataset schema indexed under Zenodo DOI 10.5281/zenodo.20265628.
ACTIVE INVESTIGATIONOngoing (2026 – 2027)

AURA: Acoustic-visual Urban Routing Architecture for Autonomous Mobile Robots

Author: Deepak RTarget: ICRA / IROS Conference Series

Investigating multimodal acoustic and visual sensor fusion frameworks to facilitate robust autonomous robot navigation and localized spatial awareness in GPS-denied, visually degraded urban canyons.

KEY CONTRIBUTIONS:
  • Cross-modal acoustic-visual feature extraction for spatial landmark localization.
  • Integration with ROS 2 Nav2 costmaps and real-time state estimators.
VERIFIED CREDENTIALS

TECHNICAL LICENSES & CERTIFICATIONS

Industrial Robotics Career Programs, IBM Machine Learning & Linux Systems

🗓 Jun 2026

Supervised Learning Methods

IBM

🗓 Jun 2026

Data Analysis Using Python

IBM

🗓 Jun 2026

Unsupervised Learning Methods

IBM

🗓 Feb 2026

CTS Jan 26 Badge

Google Cloud Skills Boost

🗓 Nov 2025

Digital Circuits

NPTEL

CREDENTIAL IDNPTEL25EE125S1154009277
#Microprocessors#Logical Design
🗓 Nov 2025

Industrial Robotics Theories for Implementation

NPTEL

CREDENTIAL IDNPTEL25ME161S1254009474
#Robotics#Kinematics
🗓 Aug 2025

Artificial Intelligence Fundamentals

IBM

🗓 Jul 2025

Computer Hardware Basics

Cisco

🗓 May 2025

Joy of Computing using Python

NPTEL

🗓 Apr 2025

Weekly Coding Challenge 26

Unstop

CREDENTIAL ID3dc431aa-a8db-4827-9b74-40e00d356b9b
🗓 Mar 2025

Create a Promotional Video using Canva

United Latino Students

CREDENTIAL IDMJL10F4I8EX0
🗓 Mar 2025

Certified Basic Resume Writer

TCS iON

🗓 Mar 2025

Build a free website with WordPress

Coursera

CREDENTIAL IDRDD8RJ6MWZEU
🗓 Feb 2025

Pearson MePro Level 10 Expert

Pearson

🗓 Feb 2022

Introduction to Programming Using Python

upGrad

CREDENTIAL IDcb560194-63da-4524-898b-8d57b772a149