Name: CAO, Yongxi
Type: User
Company: TU Delft
Bio: Student Msc. Robotics, 2022 Fall @tudelft.
B.Eng. Robot. Eng., 2018-2022 @SUSTech.
Location: Delft, the Netherlands
Blog: yongxic97.github.io
CAO, Yongxi's Projects
[ICCV 2021] Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".
A beautiful, simple, clean, and responsive Jekyll theme for academics
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
My personal process of revisiting essential topics and techniques in C++.
An evolving guide to learning Deep Learning effectively.
modifications to deeploco proj by xbpeng
Model-based design and verification for robotics.
Embedded control system of Project eSnake
Highway driving simulator incorporating NGSIM dataset using reinforcement learning
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JUCE is an open-source cross-platform C++ application framework for desktop and mobile applications, including VST, VST3, AU, AUv3, RTAS and AAX audio plug-ins.
Reproduction of OpenAI and DeepMind's "Deep Reinforcement Learning from Human Preferences"
Course notes for MIT manipulation class
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
Implementations of Reinforcement Learning and Planning algorithms
Simple http server in Rust (Windows/Mac/Linux)
Initial package for dynamic modelling of our soft robot arm
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
The course text for MIT 6.832 (and 6.832x on edX)
Config files for my GitHub profile.
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