Tao Liu (刘滔)

I am a PhD student under joint supervision between ShanghaiTech University and BIGAI, advised by Prof. Jingya Wang and Research Scientist Baoxiong Jia. My current research interests lie in Embodied AI and Vision-and-Language Navigation (VLN).

Previously, I obtained my Master degree from the Mobile Perception Lab (MPL) at ShanghaiTech University in 2025, supervised by Prof. Laurent Kneip. There I worked on SLAM and 3DGS. Earlier, I earned my B.E. from Shanghai Maritime University in 2022, working closely with Prof. Tianzheng Wang in the Intelligent Car Lab.

Github  /  Scholar  /  LinkedIn

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Internship

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Horizon Robotics
Position: Perception Algorithm Intern
Duration: December 2024 – February 2025

I participated in the 3DGS+Calib project for an online calibration solution. By taking advantage of the rendering quality and speed of 3DGS to provide an accurate calibration for Cameras and LiDAR.

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BOSCH
Position: SLAM Algorithm Intern
Duration: August 2024 – November 2024

As a strategic intern in the XC department at BOSCH (China), I was part of the vSLAM group. I worked on non-overlapping online calibration solution and was responsible for the online calibration of a multi-sensor system involving cameras and LiDAR.

Publications

EVIT: Event-based Visual-Inertial Tracking in Semi-Dense Maps Using Windowed Nonlinear Optimization
Runze Yuan, Tao Liu, Zijia Dai, Yi-Fan Zuo, Laurent Kneip
IROS 2024
Paper  |  Code  |  Video

This paper follows up on a recently introduced event-based geometric semi-dense tracking paradigm, and proposes the addition of inertial signals in order to robustify the estimation.

Motion-Aware Optical Camera Communication with Event Cameras
Hang Su, Ling Gao, Tao Liu, Laurent Kneip
RAL 2024
Paper  |  Code  |  Video

This paper introduces a dynamic visual marker and design event-based tracking algorithms to achieve fast localization and data streaming.

Competitions

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National Undergraduate Intelligent Car Competition
Category: AI Track
Award: National 2nd Prize
Video

As team leader, I guided two sophomore students in traditional control algorithms and responsible for designing hardware PCBs (control, driver, detection boards) and developing AI algorithms.

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National Undergraduate Intelligent Car Competition
Category: SLAM Track
Award: National 2nd Prize
Video

As the youngest member of the team, I initially focused on map building task. Later, I handled object detection using YOLOv5 and debugged the entire system within the ROS framework.