Hello, I'm
Arnon Chatri
อานนท์ ชาตรี · โบ๊ท
3rd Place
AAVC 2026
1st Place
KU Innovation 2026
Available
Open to work
Passionate about AI, robotics, and embedded systems. Building ML pipelines, custom drones, and hardware–software solutions that solve real‑world problems.
3rd Place
AAVC 2026
1st Place
KU Innovation 2026
Available
Open to work
Who I Am
เกี่ยวกับฉัน
Hello, my name is Arnon Chatri, or you can call me Boat. I have experience working with machine learning pipelines, AI research, and embedded systems.
I worked as a research assistant and co-authored a published research paper at Kasetsart University with Team Sean over two years.
I also built and customised a drone prototype for the Faculty of Civil Engineering— integrating AI computer vision end-to-end—which clarified my real interests and career direction.
Looking for someone for control systems, ML pipelines, or hardware projects? I'm deeply passionate about this field and would love to join your team.
AI & ML
ML pipelines & production-ready AI models
Hardware & Robotics
Drones, embedded systems, HW-SW integration
Team Player
2+ years on research & engineering teams
Autonomous Aerial Vehicle Challenge AAVC 2026
Aug 2026Drone & Computer Vision Flyhigh Team
An autonomous drone system for payload delivery and precision landing, built for the Autonomous Aerial Vehicle Challenge 2026.
Project Evidence
Key Features
- ✓ArUco landing-pad detection with an onboard camera
- ✓MAVLink mission control for autonomous payload delivery
- ✓Precision landing using Pixhawk and Jetson Nano
- ✓Geofencing, Return-to-Launch, and failsafe configuration
- ✓Flight-log analysis for stability, power reliability, and safety
Project Brief
For the Flyhigh Team at Kasetsart University, I helped design and build an autonomous drone using Pixhawk, Jetson Nano, and onboard cameras. The vision system detects ArUco landing pads, while MAVLink coordinates autonomous payload delivery and precision landing. I represented Kasetsart University at AAVC 2026 from 28–30 August 2026.
Engineering Challenge
The aircraft had to combine visual targeting, mission control, payload delivery, and landing accuracy while remaining safe under changing power, communication, and flight conditions.
Technologies
Deployment Plan
- 1Validate mission logic in simulation before hardware flight tests
- 2Run controlled field tests for detection range, landing error, and payload release
- 3Review flight logs after every test and tune power, control, and failsafe parameters
- 4Promote only validated mission profiles to competition deployment
Outcome
The Flyhigh Team was awarded 3rd Place (รางวัลชมเชยอันดับ 3) at the Autonomous Aerial Vehicle Challenge (AAVC) 2026, representing Kasetsart University from 28–30 August 2026. The team delivered a fully integrated autonomous-flight system using staged testing and flight-log analysis to achieve reliable mission performance.
CV & Resume
AI Engineer · Software Engineer · Robotics · Embedded Systems
Summary
Experienced in AI research, robotics, embedded systems, and full-stack development. Can build ML models, automated systems, and integrate APIs. Comfortable across software and hardware projects; learning quickly under pressure.
Experience
Drone & Computer Vision Engineer
Aug 2026Flyhigh Team, Kasetsart University — AAVC 2026
- Designed & built an autonomous drone using Pixhawk, Jetson Nano, and cameras
- Developed AI to detect ArUco pads; used MAVLink for autonomous payload delivery & precision landing
- Configured flight missions, geofencing, RTL, and failsafe functions
- Represented Kasetsart University at AAVC 2026 (28–30 Aug 2026)
Machine Learning Research Assistant
Nov 2024 – Aug 2026Kasetsart University
- Trained YOLO object detection system for Colletotrichum disease in rubber trees
- Used custom dataset prepared with plant pathologists at Kasetsart University
- Built LINE Bot notification system to alert farmers in high-risk zones
- Collected disease severity & weather data for a disease forecasting model
AI & Drone Engineer (Short-term Contract)
2024Freelance
- Designed & built a custom quadcopter for pigeon deterrence and aerial survey
- Integrated real-time pigeon detection via onboard AI computer vision
- Developed autonomous flight control with an Arduino-based embedded system
- Implemented aerial photography capabilities for civil engineering inspections
Education
B.Eng. Computer Engineering
Kasetsart University
Technical Skills
Languages
AI / ML
Robotics
Web & Tools
Get In Touch
ติดต่อฉัน — Let's work together!
Send a Message
Your message goes straight to boat.arnonchatri@gmail.com
Let's Collaborate!
Always interested in new projects and opportunities. Whether it's collaborating on a project or bringing ML expertise — feel free to reach out!