CASE STUDY // SYS-NIDAR-2025-SYSTEMNational Ignite Prize Winner
NIDAR 2025 Autonomous Disaster Relief Drone System
Award-winning dual-drone autonomous platform for disaster response, survivor localization, and medical payload dropping.
#AUTONOMY#AERIAL#AI#RESEARCH
DEVELOPMENT YEAR2025
MY ROLESystem Architect, Patent Author & Flight Operations Lead
TEAM STRUCTUREAero-Modelling Club Project Lead
VALIDATION STATUSNational Ignite Prize Winner
THE ENGINEERING PROBLEM
During major disasters, ground access is severed, requiring autonomous aerial reconnaissance and targeted survivor aid deployment.
THE ARCHITECTURAL SOLUTION
Engineered a coordinated dual-drone architecture where lead UAV performs high-altitude computer vision mapping while follower drone deploys aid packages.
SYSTEM OVERVIEW & ARCHITECTURE
Subject of an official Indian Patent filing and Ignite Prize winner at NIDAR'25 national aerospace competition.
SYSTEM ARCHITECTURE BLOCK DIAGRAM FLOW:
Reconnaissance Drone (Edge CV Model) → [MAVLink Network / Ground Link] → Target Payload Drone → Autonomous Precision Release.
KEY TECHNICAL HIGHLIGHTS:
- ✓Patented dual-drone mission coordination protocol over MAVLink network.
- ✓Onboard computer vision detection models trained on human thermal and RGB features.
HARDWARE & ELECTRONICS
- Custom Carbon Fiber Quadrotor Frames
- PX4 Flight Stacks
- NVIDIA Jetson / Pi Edge Compute
- Thermal Camera Payloads
SOFTWARE & FIRMWARE
- ROS2
- PX4
- Python
- YOLOv8
- OpenCV
- MAVLink
- QGroundControl
ALGORITHMS & CONTROL LOOPS
- Coordinated Mission Task Allocation
- YOLO Edge Survivor Detection
- Precision GPS Drop Calculation
COMMUNICATION PROTOCOLS
- MAVLink 2.0 Network
- UDP / IP
- UART Serial
ENGINEERING CHALLENGES OVERCOME
- Synchronizing real-time coordinate targets across two autonomous airframes over low-bandwidth RF links.
MY DIRECT CONTRIBUTIONS
- Co-authored Indian Patent specification, architected drone-to-drone mission payload protocol, and led team flight validation.
VALIDATED SYSTEM RESULTS
- ▸Won Ignite Prize at NIDAR'25; successfully validated multi-UAV disaster mission scenario.
KEY ENGINEERING LESSONS LEARNED
- ▸Robust fail-safe fallbacks are crucial when multiple autonomous vehicles share mission coordination networks.