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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
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Posts
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Blog Post number 1
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portfolio
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publications
Toward a Telescopic Steerable Robotic Needle for Minimally Invasive Tissue Biopsy
Published in IEEE Robotics and Automation Letters, 6(2): 1989–1996, 2020
Authors: Boshen Qi, Ziqing Yu, Zahra K. Varnamkhasti, Yizhi Zhou, Jun Sheng
Distributed Multi-Robot Flocking Based on Acoustic Doppler Effect
Published in 2023 62nd IEEE Conference on Decision and Control (CDC), pp. 6406-6411, 2020
Authors: Yizhi Zhou, Cameron Nowzari, Xuan Wang
Distributed Invariant Extended Kalman Filter Using Lie Groups: Algorithm and Experiments
Published in IEEE Transactions on Control Systems Technology, 31(6): 2777–2789, 2023
Authors: Jie Xu, Pengxiang Zhu, Yizhi Zhou, Wei Ren.
D3g: Learning Multi-Robot Coordination From Demonstrations
Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8898–8904, 2024
Authors: Yizhi Zhou, Wanxin Jin, Xuan Wang
Consistent Cooperative Visual-Inertial Navigation based on Matrix Lie Group
Published in 2025 American Control Conference (ACC), pp. 1204-1209, 2025
Authors: Yizhi Zhou, Wanxin Jin, Xuan Wang
CVIRO: A Consistent and Tightly-Coupled Visual-Inertial-Ranging Odometry on Lie Groups
Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
Authors: Yizhi Zhou, Jie Xu, Jiawei Xia, Zechen Hu, Weizi Li, Xuan Wang
Robust Online Calibration for UWB-Aided Visual-Inertial Navigation with Bias Correction
Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
Authors: Yizhi Zhou, Ziwei Kang, Jiawei Xia, Xuan Wang
talks
D3G: Learning multi-robot coordination from demonstrations
Published:
In this talk, I present D3G, a novel framework for learning multi-robot coordination from demonstrations. The approach leverages imitation learning to enable groups of robots to perform complex collaborative tasks efficiently and robustly. I discuss the key challenges in multi-robot coordination, our proposed solution, experimental results on real-world robotic platforms, and future directions for scalable autonomous systems.
Consistent Cooperative Visual-Inertial Navigation based on Matrix Lie Group
Published:
In this talk, I introduce a consistent cooperative visual-inertial navigation framework based on Matrix Lie Group theory. The proposed approach enables multiple agents to achieve accurate and robust state estimation by fusing visual and inertial measurements in a cooperative manner. I discuss the theoretical foundations, algorithmic design, and experimental validation on real-world robotic platforms, highlighting improvements in consistency and scalability for multi-agent navigation.
teaching
GMU EE530 Senior Design Project (Fall 2024)
Undergraduate course, ECE Department, George Mason University, 1900
As part of my teaching experience, I supervised undergraduate students in the GMU EE530 Senior Design Project, guiding them through the process of developing and completing their graduation projects. My role included providing technical mentorship, project management advice, and support in solving engineering challenges.