Wireless Robotics Platform (FR3 / TurtleBot4 & Jackal UGV)
I am building and validating a 10-GHz FR3 robotic measurement platform for closed-loop localization and navigation experiments. The system combines Xilinx RFSoC 4×2 boards, Pi-Radio FR3 front ends, Vivaldi antennas, 2D LiDAR/RGB sensing, fixed and linear-track/D48 measurements, TurtleBot4 transmitter mobility, Jackal UGV receiver mobility, and Vicon ground truth under controlled LOS/NLOS transitions.
The validation setup provides repeatable ground truth for robot motion and obstacle-induced LOS/NLOS experiments.
The demo shows the robotic measurement platform executing controlled motion while RF sensing data are collected.
This public demo shows the TurtleBot4-mounted FR3 hardware operating in a live measurement setting.
Media & Public Demonstrations
Interview recorded at the Brooklyn 6G Summit 2025.
At the 2025 Brooklyn 6G Summit, I demonstrated an FR3-based robotic sensing and localization platform that combines TurtleBot4 mobility, Pi-Radio front ends, angle-of-arrival measurements, and SLAM-based mapping. The demonstration showed how RF observations can support indoor positioning when visual information is incomplete or unavailable.
System capabilities
- RFSoC transmit/receive waveform generation, capture, synchronization, channel estimation, SNR estimation, and AoA processing.
- Pi-Radio/Sivers front-end control, remote TCP/REST control, and synchronized physical metadata logging.
- Scripted TurtleBot4, linear-track, and D48 pan-tilt motion for reproducible measurement grids.
- Physical support for MC-CLE/LOCUS-DT posterior localization and wireless-aware navigation experiments.
The hardware bench combines the Pi-Radio FR3 front end, RFSoC 4×2 baseband, Vivaldi antennas, and local compute/control equipment.
The hardware photo shows the deployed TurtleBot4 stack with the RF front end, compute, power, and control layers integrated on the robot.
Haozhe Lei (Graduate Student Member, IEEE) is a Ph.D. candidate in Electrical and Computer Engineering at New York University, advised by Professor Sundeep Rangan in NYU WIRELESS. He received the B.E. degree in electrical engineering and automation from China Agricultural University in 2019 and the M.S. degree in computer engineering from NYU in 2022. His research develops uncertainty-aware wireless intelligence for embodied autonomy and adaptive 6G systems, combining algorithms, digital twins, and physical testbeds to transform sparse RF and multimodal observations into calibrated spatial beliefs and closed-loop decisions.
His current work includes MC-CLE and LOCUS-DT for posterior RF localization, PIRL and wireless digital-twin priors for zero-shot robot navigation, MCMB-HDT for closed-loop multi-band handset adaptation, and object-centric graph memory for multimodal spatial reasoning. He also builds FR3/mmWave RFSoC/Pi-Radio channel-sounding systems with TurtleBot4 and Jackal UGV platforms. He received the 2023 Ernst Weber Fellowship from the NYU Tandon School of Engineering.