About Me

I am a master student at Southern University of Science and Technology (SUSTech), advised by Dr. Wei Zhang and Dr. Hua Chen. Before that, I obtained my B.E. degree in Robotics Engineering in 2021 from SUSTech. Currently, my research interests lie in perceptive locomotion of legged robot and deep reinforcement learning.

Publications

Overview	Information
	GeoReF: Geometric Alignment Across Shape Variation for Category-level Object Pose Refinement Linfang Zheng, Tze Ho Elden Tse, Chen Wang, Yinghan Sun, Esha Dasgupta, Hua Chen, Aleš Leonardis, Wei Zhang, Hyung Jin Chang CVPR, 2024
	Multi-Resolution Planar Region Extraction for Uneven Terrains Yinghan Sun, Linfang Zheng, Hua Chen, Wei Zhang ICRA, 2024 [arXiv]
	HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimation Linfang Zheng, Chen Wang, Yinghan Sun, Esha Dasgupta, Hua Chen, Aleš Leonardis, Wei Zhang, Hyung Jin Chang CVPR, 2023 [project page] [paper] [arXiv] [code] [video]

Selected Projects

Overview	Information
	Blind Locomotion on Uneven Terrains for Quadrupedal Robot Part of my current research project.
	Quadruped Locomotion Using Convex Model Predictive Control Implemented the MIT’s solution using Python. [code]
	Kinematics-Aware Bipedal Robot Switch Light Second Prize | WAIC 2020 · Humanoid Service Robot Simulation Competition
	3-DoF Ball on Plate Using Closed Loop Stepper Motors Yinghan Sun, Daifeng Li, Shilong Yao Course project in ME425 Sensing Technology, SUSTech
	A Gecko-inspired Soft-and-rigid Climbing Robot Yinghan Sun, Zhuotong Yu, Yichen Song, Shaoqian Li, Bowen Shen Course project in ME337 Advanced Actuation for Robots, SUSTech

Teaching

• Teaching assistant in ME424 Modern Control and Estimation, SUSTech.
  [course website] [recordings (Youtube)] [recordings (Bilibili)]
  Course introduction: This course will introduce the students to the fundamental concepts and methods in modern control and estimation theory. Topics include state-space modeling of dynamical systems, least-square estimation and system identification, state-feedback and output-feedback controller design, observer design, linear quadratic regulators, and Kalman filter. The course will also connect these control and estimation methods to applications in robotics, mechanical, electrical, and aerospace systems.