Wearable Motion Capture System
Real-time hardware-to-software motion capture system using ESP32-S3, MicroPython, UDP/TCP, Node.js, SvelteKit, and Three.js.
The Problem
Real-time motion capture requires reliable communication between wearable sensor nodes, a receiver unit, backend tooling, and a browser-based visualization layer while keeping latency low and the system debuggable.
My Approach
Architected a complete hardware-to-software motion capture ecosystem using wearable sensor nodes and a wireless receiver unit. Built ESP32-S3 firmware with MicroPython, streamed sensor data using UDP, used TCP for command/control communication, and created a SvelteKit + Three.js dashboard for real-time 3D visualization.
Technical Decisions
Separated low-latency data streaming from reliable control messaging by using UDP for real-time motion data and TCP for command/control flows. Built a Node.js CLI diagnostic tool to benchmark, stress test, connection test, and inspect raw serial streams.
Result
Created a working real-time motion capture system with browser-based skeletal visualization, quaternion-based motion rendering, I2C recovery logic, serial diagnostics, networking troubleshooting, and backend data handling.