CASE STUDY // SYS-MEDRESQValidated System Prototype
MedResQ / Medical Diagnostic & Delivery Drone
Autonomous aerial medical diagnostic and emergency supply payload delivery platform.
#AERIAL#AUTONOMY#AI#PRODUCT_DEVELOPMENT
DEVELOPMENT YEAR2025
MY ROLEEnd-to-End System Design, Flight Firmware & AI Vision Integration
TEAM STRUCTURELead Systems Architect & Robotics Engineer
VALIDATION STATUSValidated System Prototype
THE ENGINEERING PROBLEM
Critical medical supplies and rapid diagnostic telemetry in remote or disaster-stricken terrains often face catastrophic ground transportation delays.
THE ARCHITECTURAL SOLUTION
Engineered an autonomous dual-capability aerial platform equipped with edge computer vision for survivor landing site identification and a drop-mechanism payload bay.
SYSTEM OVERVIEW & ARCHITECTURE
MedResQ integrates PX4 autopilot firmware over MAVLink with a companion computer executing real-time object detection models for autonomous emergency delivery.
SYSTEM ARCHITECTURE BLOCK DIAGRAM FLOW:
Companion Computer (Raspberry Pi/Jetson) ←[MAVLink]→ PX4 Flight Controller → ESCs & Actuators. Edge CV models detect landing markers and release diagnostic packages dynamically.
KEY TECHNICAL HIGHLIGHTS:
- ✓Real-time object detection on edge compute hardware for landing zone validation.
- ✓Custom MAVLink offboard control loops for obstacle avoidance and precision hover.
- ✓Integrated emergency parachute payload deployment system.
HARDWARE & ELECTRONICS
- Custom Carbon-Fiber Frame
- PX4 Flight Controller
- Companion Single Board Computer
- Servo Payload Release Mechanism
- LiPo Telemetry Sensors
SOFTWARE & FIRMWARE
- PX4 Autopilot
- ROS2 Humble
- Python OpenCV
- YOLOv8 Edge Model
- MAVSDK
ALGORITHMS & CONTROL LOOPS
- Autonomous Path Planning (A*)
- Visual Marker Precision Hover
- Kalman Filter Sensor Fusion
COMMUNICATION PROTOCOLS
- MAVLink 2.0
- UART
- I2C
- UDP Telemetry
ENGINEERING CHALLENGES OVERCOME
- Mitigating electromagnetic interference (EMI) between High-Amp ESC power traces and sensitive GPS/IMU sensors.
- Maintaining low-latency offboard control during rapid wind gust disturbances.
MY DIRECT CONTRIBUTIONS
- Designed full mechanical UAV frame, payload drop mechanism, and power distribution PCB.
- Programmed companion computer offboard control scripts in Python using ROS2 and MAVLink.
- Tested and validated field flight performance in multi-rotor hover and payload delivery modes.
VALIDATED SYSTEM RESULTS
- ▸Achieved autonomous landing marker detection and precise delivery release within tight margin tolerances.
KEY ENGINEERING LESSONS LEARNED
- ▸Isolating power distribution from signal buses is imperative for reliable GPS locking in high-current aerospace platforms.