Mingjin Lu.

UWB TDoA Real-time Localization

Developing an indoor tracking prototype for tagged robots and vehicles using ultra-wideband radio and time difference of arrival (TDoA), as a solo EC601 project.

The planned system combines DWM3000 modules and ESP32-C3 controllers with a computer-based localization pipeline, live map, configurable zones, and tracking alerts. Current work focuses on hardware integration, anchor clock synchronization, and evaluation planning.

View project on GitHub

EC545 Debris-Clearing Rescue Robot

Collaborating in a four-person team on a mobile robot concept that detects and moves small obstacles from a planned path, supporting a controlled disaster-response demonstration.

Contributing the high-level system architecture, connecting base and wrist cameras, a mobile platform, and an SO-101 arm trained through teleoperation and imitation learning. The project is in the proposal and system-design stage, with planned checks for failed grasps and blocked paths.

FPGA Signal Processing Pipeline

Designed a 25-tap complex FIR and CORDIC accelerator on a Zynq FPGA to calculate magnitude and phase from complex input signals.

Loop unrolling, array partitioning, and HLS pipelining raised estimated Fmax from 141.7 to 165.6 MHz. Fixed-width and fixed-point arithmetic reduced DSP use by 93%, FFs by 86%, and LUTs by 83% versus the standard integer/double implementation.

8-Bit Carry Skip Adder

Architected a two-stage pipelined CMOS adder in Cadence Virtuoso, verified with transient simulation and worst-case timing analysis.

Debugged bus timing glitches and optimized pipeline register behavior to improve signal integrity and timing consistency.

Permafrost Freeze & Thaw

Led a five-person capstone team to build a Peltier-based soil freeze–thaw platform supporting AFOSR-funded permafrost research in Alaska.

Integrated Keysight VNA measurements to analyze S11 frequency response during thermal cycling, enabling repeatable laboratory thermal and RF characterization experiments.

Smart Auto Camera

Built an autonomous object-tracking camera using a Raspberry Pi 5 and ESP32-controlled servos.

Combined Python, OpenCV motion detection, and YOLO object recognition with a custom soldered control circuit and 3D-printed camera and servo mounts.