Zhengxiao Han

I am a M.Sc. Student in Robotics at Northwestern Univeristy.

Previously, I spent a gap year as a Research Assistant at Center on Frontiers of Computing Studies, Peking University, under the supervision of Prof. Hao Dong.

I completed my Bachelor's degree in 2023 at BUCT, where I used to lead the SIE Robotics Club.

Before getting the B.Eng., I spent two years at DISCOVER Lab, Tsinghua University as a Research Intern, under the supervision of Prof. Guyue Zhou.

Proudly, I am a core contributor to Mini Pupper, an open-source quadruped robot.

LinkedIn  /  GitHub  /  X  /  Google Scholar  /  Email

Research & Engineering

I have always been working on Robotics. Currently I'm interested in Embodied AI.

Constructed a 7-DOF humanoid robotic arm with dexterous hands equipped with tactile sensors for data collection, and interfaced it with ROS Control and MoveIt. All work was done by me independently. We will work on encoding visual, tactile (not vision-based) and joint signals for imitation learning and deploy learned policies on real robots.

Achived hardware design of a new 6-DOF robotic arm, and interfaced all hardware under ROS Control and MoveIt. Interfaced the robotic arm with GraspNet and achived a grasping demo. All work was done by me independently.

Achived hardware design of a 6-DOF robotic arm and a 2-finger adaptive parallel gripper (same capability as Robotiq 2f-85 Gripper). Constructed a robotic arm SDK with CMake, and interfaced the lib with ROS and Isaac Sim.

Inspired by ALOHA, we proposed an improved bimanual demonstration system. Constructed the SDK using C++ and CMake. Utilized KDL to solve kinematic and dynamic problems, then achived gravity compensation based on inverse dynamics. Designed a parallel two-finger gripper based on rack-gear structures.

Developed all the ROS 2 (Humble) software suite including Locomotion, SLAM, Navigation, and CV functions. Deployed Cartographer with an Extended Kalman Filter (EKF) to fuse IMU data and LiDAR odometry, enhancing the robostness and accuracy of Mini Pupper's localization system.

We developed an intelligent desktop operating robot designed to assist humans in their daily lives by comprehending natural language with large language models and performing a variety of desktop-related tasks.

Cooperated with Baidu Apollo and MARS Lab at Tsinghua University. We propose to introduce a tailored Model Predictive Control (MPC) module as a rescue into the state-of-the art interactive trajectory prediction model M2I. Notably, our method can effectively address the Out-of-Domain (OOD) problem in long-term simulation by enforcing a flexible regularization that admits the replayed data, while still enjoying the diversity of data-driven predictions.

We present a large-scale interactive trajectory prediction dataset named INT2 for INTeractive trajectory prediction at INTersections. INT2 includes 612,000 scenes, each lasting 1 minute, containing up to 10,200 hours of data. We benchmark the best open-sourced interactive trajectory prediction method on INT2 and Waymo Open Dataset, under in-domain and cross-domain settings.

Utilized Pure Pursuit algorithm for multi-robot formation control, which was tested in both real world and Isaac Sim. Utilized an EKF-based 2D LiDAR localization system as the odometry. Utilized KDL for solving kinematic problems of our own 6-DOF robotic arm, and combined it with the odometry, achieving Chiken-Head Mode. Combined all the functions above, and constructed a multi-robot cooperative system to carry a box in Isaac Sim.

Deployed an Extended Kalman Filter (EKF) alongside an omnidirectional motion model for state projection and correction using sensor data, including IMU and odometry. Utilized A* algorithm for global path planning and Timed Elastic Band (TEB) algorithm for local path planning. Utilized ArUco library for detecting boxes' poses.

Inspired by Stanford's open-source quadruped robot Pupper, I designed my own mechanical hardware, mainly improved its leg structures. After that, I was contacted by Mini Pupper's team and joined them. We developed the first product together. I independently developed all the ROS software suite including Locomotion, SLAM, Navigation, and CV functions. We crowd-funded $500,000 on Kickstarter when I was a junior.

Education

September, 2024.
Design and source code from Jon Barron's website.