University of California, Berkeley, USA
Master of Mechanical Engineering (Robotics)
2026.8 - Present
Admitted for Fall 2026.
Beijing University of Chemical Technology, Beijing, China
Bachelor of Engineering, Mechanical Design and Its Automation (Robotics)
2022.9 - 2026.6
GPA: 3.7/4.0 Rank: Top 5% Former President of SIE Robotics Club.
JD Explore Academy, JD.com, Inc
Embodied AI Algorithm Intern Mentor: Dr.Lvsong Li, Dr. Jiangmiao Pang 2026.3-2026.6
Responsible for hardware debugging, data acquisition system development, model training and deployment based on the ARX5 ALOHA dual-arm robot platform.
Participated in the research on reinforcement learning post-training in robotic VLA models and the development of 3D/4D scene models for embodied intelligence.
Institute for AI Industry Research, Tsinghua University
Research Intern Advisor: Dr. Yongliang Shi, Dr. Weining Lu 2024.12-2026.2
Responsible for the development of the Robust LiDAR-Inertial-Thermal SLAM system and other Visual-Inertial Odometry.
Participated in the research of a multimodal framework for robotic kitchen manipulation, including the integration of tactile and thermal imaging sensors into robot imitation learning.
While world models evaluate future states well, effective continuous control relies on generating good candidate actions. Existing planners either search arbitrarily or require bloated architectures (e.g., VLMs) for action priors. We introduce PRISM, a simple, task-agnostic framework. Attached to a frozen JEPA encoder, a lightweight MLP predicts a Gaussian action prior. At plan time, a closed-form Product-of-Gaussians update integrates this prior to guide sampling based on confidence.
Thermal imaging handles adverse conditions but suffers from AGC and low contrast, violating brightness constancy. To solve this, we propose PL-LIT, a general LiDAR-Inertial-Thermal SLAM system compatible with both visible and thermal cameras. Built on an ESIKF framework, it integrates online photometric calibration with deep point-line feature extraction and robust line constraints. Furthermore, it constructs a probabilistic thermal voxel map to support real-time anomaly detection.
CVIRO: A Consistent and Tightly-Coupled Visual-Inertial-Ranging Odometry on Lie Groups Yizhi Zhou,
Ziwei Kang,
Jiawei Xia,
Xuan Wangβ International Conference on Intelligent Robots and Systems 2025 (IROS) [Paper][Video]
This paper proposes a consistent
and tightly-coupled visual-inertial-ranging odometry system based on the Lie group. Our method incorporates the
UWB anchor state into the system state, explicitly accounting
for UWB calibration uncertainty and enabling the joint and
consistent estimation of both robot and anchor states.
Robust Online Calibration for UWB-Aided Visual-Inertial Navigation with Bias Correction Yizhi Zhou,
Jie Xu,
Jiawei Xia,
Zechen Hu,
Xuan Wangβ International Conference on Intelligent Robots and Systems 2025 (IROS) [Paper][Video]
This paper proposes a robust online calibration method for UWB anchors in Visual-Inertial Navigation Systems. Based on MSCKF, our approach uses stochastic optimization for reliable initialization and a Schmidt Kalman Filter for online refinement.
Our team won first place in the Flexible Manipulation Track at ICRA 2026 WBCD Challenge, held in Vienna, Austria. Our approach is based on reinforcement learning fine-tuning the pre-trained Vision-Language-Action (VLA) mode. Ultimately, the model achieved a high success rate on the deformable/flexible clothing tasks.
Conducted reinforcement learning-post training of robotics manipulation models Jiawei Xia
This project tried two ways about reinforcement learning post-training on robotic models. Firstly, we used the DAgger framework and positive/negative labeling to conduct rl post-training on the vision language action model, enabling the robot to perform the clothes-folding task. Secondly, we leverage sparse task success rewards and an off-policy actor-critic framework to fine-tune policy in simulation environment.
RoboCup@Home: Development of an Intelligent Home Service Robot Based on ROS Jiawei Xia,
Xianglei Dong,
Wengcong Zhang,
Boyi Zhang,
Yutong Sun
Developed an intelligent home service robot using a Kinova Gen2 arm and an Azure Kinect camera on ROS Noetic, with functions including guest reception and guidance, voice interaction, object recognition, and room cleaning. Used Gemini, SAM2, and GraspNet to estimate object pose and grasp objects. Controlled the arm using Actionlib and MoveIt. Applied FAST-LIO2 with Livox MID-360 for indoor mapping and localization.
Based on Kongfubot, used inverse kinematics retargeting and reinforcement learning to enable humanoid robots to imitate highly-dynamic behaviors (e.g., kungfu, dancing). Developed sim2sim in MuJoCo and sim2real with Unitree SDK, successfully deploying the framework on the Unitree G1 robot.
RoboMaster University League 1v1 Combat Competition
Yutao Guo*,
Hanhong Fu*,
Jiawei Xia
Used PnP to calculate the 3D position of the armor plate, and used Kalman filtering for tracking; The robot used four M3508 motors for the chassis and two M6020 motors for the turret, controlled via CAN communication and PID algorithms for current, speed, and position loops. Used feedforward PID to improve the gimbal drive and achieve gravity compensation.
ICRA 2024 RoboMaster Sim2real Challenge: In Habitat sim environment in docker provided by organizers, utilized ArUco for detecting poses of boxes, extracted the transformation and rotation matrices of box from solvePnP. Deployed an Extended Kalman Filter alongside an omnidirectional motion model for state estimation using sensor data, including IMU, odometry and depthimage to laserscan.