News

• [2026.08] 🤖 I start my master's degree at UC Berkeley.

• [2026.06] 🏆 Our team won First Place in the Flexible Manipulation Track at ICRA 2026 WBCD Challenge, Vienna, Austria.

• [2026.03] 🎉 I joined JD Explore Academy as an Embodied AI Algorithm Intern, Beijing, China.

• [2025.07] 🎉 I was honored to receive First Prize in the Embodied AI Bootcamp organized by HKCRC, Hong Kong, China.

• [2025.04] 🏆 Our team won Third Prize in the DJI Technology RoboMaster Competition 2025, Shandong, China.

• [2024.12] 🎉 I joined the Institute for AI Industry Research, Tsinghua University as an Intern, Beijing, China.

• [2024.11] 🎉 I was honored to receive the Xiaomi Scholarship.

• [2024.06] 🏆 Our team won Second Prize in RoboCup@Home 2024, Fujian, China.

Research Experience

Researching robotic dexterous manipulation skill learning and reinforcement learning policy post training.

Developed data, training, and deployment pipelines for dual-arm manipulation, with a focus on 3D/4D World model and reinforcement learning post-training for robotic models.

Developed Robust LiDAR-inertial-thermal SLAM and explored tactile and thermal sensing for robot imitation learning.

Developed robust online UWB-anchor calibration for improved visual-inertial robot localization.

Publications

* : Equal contribution; †: Corresponding author(s)

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.

We introduce DexNinja, a Real2Sim2Real data engine for robust bimanual dexterous food cutting. DexNinja extracts object-centric knife-motion templates, generates physically consistent data with deformable cutting simulation, and trains a stage-conditioned vision-tactile ACT policy with decoupled arm/hand actions and adaptive action chunking.

We propose PL-LIT, a general LiDAR-Inertial-Thermal SLAM system. PL-LIT combines an online photometric calibration module with a deep neural network for point-line feature extraction. For state estimation, we design a tightly coupled LiDAR-Inertial-Thermal formulation within an Error-State Iterated Kalman Filter. In addition, PL-LIT builds a probabilistic thermal-intensity voxel map

This paper proposes a consistent and tightly-coupled visual-inertial-ranging odometry system based on the Lie group.

This paper proposes a robust online calibration method for UWB anchors in Visual-Inertial Navigation Systems.

Research Projects

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.

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 vla model. Secondly, we leverage sparse task success rewards and an off-policy actor-critic framework to fine-tune policy in simulation environment.

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.

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.

Honours & Awards

• 2026 Beijing Outstanding Undergraduate Graduate
• 2025 First Prize in the Embodied AI Entrepreneurship Bootcamp organised by Hong Kong Center for Construction Robotics
• 2025 Third Prize in DJI Technology RoboMaster University League Competition 2025, China, Shandong Province
• 2024 Xiaomi Scholarship
• 2024 Second Prize in Robocup@Home Competition (leader)
• 2024 Second Prize in China iCAN Innovation Contest (leader)
• 2023 Beijing University of Chemical Technology Excellent Student Leader
• 2021 First Prize in DJI Technology RoboMaster Youth East China League Competition

Leadership & Activities

• Leader of the SIE Robotics Club
• Signed Photographer for 500px and Visual China
• Leader of the Comprehensive Office, BUCT Student Union
• Member of BUCT SIE Basketball Team
• Teaching Assistant of Robotic Workshop at BUCT

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