Zhanyu Guo

Hangzhou City, Zhejiang, China

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Summary

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Rockstar

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Top School

Zhanyu Guo is an electrical and electronic engineer with five years of hands-on experience bridging research and robotics software, currently pursuing graduate studies at Caltech after a BE from Southwest Jiaotong University. He is fluent in C, C++, MATLAB, and Python, and has applied those skills to motion planning and simulation work—contributing ROS planner implementations for graph-based algorithms (including D* and LPA*) used for AGV/AMR navigation. During a research assistantship at Leeds he built 3D motion and nerve-signal datasets and implemented a 3D twisting mechanism for biomechanical worm models, reflecting a knack for combining simulation, machine learning, and biological insight. Known for strong analytical thinking and independent study, he has interned on simulation and ML projects with Prof. Netta Cohen and consistently brings creative, practical solutions to novel engineering challenges.

5 years of coding experience

Bachelor of Engineering - BE, Electrical and Electronics Engineering, Bachelor of Engineering - BE, Electrical and Electronics Engineering at Southwest Jiaotong University

California Institute of Technology

Chinese, English

Stackoverflow

Stats

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Github Skills (8)

pathfinding10

c-language10

cprogramming-language10

motion-planning10

python10

ros10

astar9

robotics9

Programming languages (2)

C++Python

Github contributions (5)

ai-winter/ros_motion_planning

Jan 2023 - Mar 2023

Motion planning and Navigation of AGV/AMR：ROS planner plugin implementation of A*, JPS, D*, LPA*, D* Lite, Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, ACO, PSO, Voronoi, PID, LQR, MPC, DWA, APF, Pure Pursuit etc.

Role in this project:

Back-end Developer

Contributions:62 commits, 3 PRs, 148 pushes in 2 months

Contributions summary:Zhanyu primarily contributed to implementing global motion planning features, specifically focusing on integrating and implementing different graph-based planning algorithms within the ROS environment. This involved adding support for D* and LPA* planners, alongside existing A* and JPS implementations, which expanded the motion planning capabilities. The commits show the integration of new algorithms by modifying and creating C++ and Python code, as well as updating the launch files.

ant-colony-optimizationartificial-potential-fieldastardstardstar-lite

ZhanyuGuo/smartcar_ws

Jan 2021 - Mar 2023

Contributions:6 commits, 2 pushes, 1 branch in 2 years 2 months

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