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Kangyao Huang  

PhD Candidate | AI Researcher | Aerospace & Robotics Engineer


I am Kangyao Huang (黄康尧 in Chinese) from China, working towards AI and robotics research and application. Currently, I am pursuing a PhD degree in Computer Science at Tsinghua University(THU) under the supervision of Prof. Huaping Liu. Besides, I also hold an MRes degree in Control & Systems Engineering from ACSE, the University of Sheffield(UoS), UK., supervised by Prof. John Oyekan, and a BEng degree in Aircraft Design & Engineering from Northwestern Polytechnical University (NWPU), China. I had several years start-up experience in aerospace and robotics sectors, serving as CEO, technical director, and robotics engineer.

I have experience in EAI, UAV, and autonomous driving. I lead the development of the first generation of Tsinghua Mengshi intelligent flying car which is the world's first electric manned rotorcraft amphibious ground-aerial vehicle with integrated intelligent driving function. My current research interest is in Embodied AI for virtual and real world practice. I also follow ideas on aerial robotics and reconstruction. I am doing a startup @emNavi Tech, focusing on the EAI enhanced navigation and related sensors. If you have any ideas, please do not hesitate to email me directly.

Top Open-source Projects


emNavi

emNavi derives from "Embodied Navigation". The vision of emNavi is to make navigation more intelligent. Besides, emNavi is an open-sourced project that re-construct and optimize the navigation-related SoTA (state of the art) algorithms and apply them on robots, especially aerial robots, to promote the implementation of Embodied AI on mobile robots.


emNavi Quadrotor DRL Simulation Platform

AirGym is an open souce Python quadrotor simulator based on IsaacGym, a part of AirGym series Sim-to-Real working flow. It provides a high-fidelity dynamics and Deep Reinforcement Learning (DRL) framework for quadrotor robot learning research. Furthermore, we also provide toolkits for transferring policy from AirGym simulator to the real quadrotor emNavi-X152b, making Sim-to-Real possible.


Book


cover

Embodied Multi-Agent Systems

Huaping Liu, Xinzhu Liu, Kangyao Huang, Di Guo

This book focuses on active perception and interactive learning for embodied multi-agent systems. The remarkable reasoning, perception, and decision-making capabilities demonstrated by LLM in recent years have brought significant opportunities for the exploration of artificial general intelligence (AGI). This results in the development of increasingly larger models and a higher consumption of data. The ultimate goal is to achieve AGI through a unified brain model. However, when it comes to embodied agents, this strategy encounters considerable challenges due to the variety in morphology and function among these agents. It is neither feasible nor desirable to expect all embodied agents to conform to a single morphology. Instead, we should embrace the principles of biodiversity, promoting the existence, collaboration, and interaction of various forms. This recognition has motivated our research into embodied multi-agent systems. During this process, we have realized that active perception, along with the interactive learning capabilities that stem from it, plays a crucial role in fostering collaboration and synergy among multiple embodied agents.

We would like to thank Prof. Angelo Cangelosi, Prof. David Hsu, Prof. John Aloimonos who provide lots of support. We would like to express our gratitude to Dr. Hongbo Li from Geek+ and Dr. Tianlei Zhang from TrunkTech for their invaluable support in our study of embodied multi-agent collaboration. Additionally, we would like to express our sincere gratitude to Chenxu Wang, Xinghang Li, Juan Wang, Peiyan Li, Pingcheng Jian, and Chuye Hong for their significant assistance in preparing the figures and proofreading the book.

Publications


A General Infrastructure and Workflow for Quadrotor Deep Reinforcement Learning and Reality Deployment

Kangyao Huang*, Hao Wang*, Yu Luo, Jingyu Chen, Jintao Chen, Xiangkui Zhang, Xiangyang Ji, Huaping Liu * contribute equally to this work

arXiv


Learning a Distributed Hierarchical Locomotion Controller for Embodied Cooperation

Chuye Hong*, Kangyao Huang*, Huaping Liu * contribute equally to this work

Conference on Robot Learning (CoRL) 2024


CompetEvo: Towards Morphological Evolution from Competition

Kangyao Huang, Di Guo, Xinyu Zhang, Xiangyang Ji, Huaping Liu

International Joint Conference on Artificial Intelligence (IJCAI) 2024


Stimulate the Potential of Robots via Competition

Kangyao Huang, Di Guo, Xinyu Zhang, Xiangyang Ji, Huaping Liu

IEEE International Conference on Robotics and Automation (ICRA) 2024


A Multi-modal Deformable Land-air Robot for Complex Environments

Xinyu Zhang, Yuanhao Huang, Kangyao Huang, Xiaoyu Wang, Dafeng Jin, Huaping Liu, Jun Li

IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) 2023


Coupled Modeling and Fusion Control for a Multi-modal Deformable Land-air Robot

Xinyu Zhang, Yuanhao Huang, Kangyao Huang, Ziqi Zhao, Jingwei Li, Huaping Liu, Jun Li

Submitted to RAS



Path Planning for Air-Ground Robot Considering Modal Switching Point Optimization

Xiaoyu Wang, Kangyao Huang, Xinyu Zhang, Honglin Sun, Wenzhuo Liu, Huaping Liu, Jun Li

International Conference on Unmanned Aircraft Systems (ICUAS) 2023


智能飞行汽车关键技术及发展趋势 - State-of-the-art and Technical Trends of Intelligent Flying Cars

Xinyu Zhang, Songsong Rong, Jun Li, Deyi Li, Huaping Liu, Yuanhao Huang, Kangyao Huang

中国科学:技术科学, Science China-Technological Sciences, 2023 Cover Paper


Intelligent Amphibious Ground-aerial Vehicles: State of the Art Technology for Future Transportation

Xinyu Zhang, Jiangeng Huang, Yuanhao Huang, Kangyao Huang, Lei Yang, Yan Han, Li Wang, Huaping Liu, Jianxi Luo, Jun Li

IEEE Transactions on Intelligent Vehicles (T-IV) 2022 IF: 14


Bio-inspired Multi-agent Model and Optimization Strategy for Collaborative Aerial Transport

Kangyao Huang, Jingyu Chen, John Oyekan, Xinyu Zhang

Chinese Intelligent Automation Conference (CIAC) 2021 Best Student Paper


Decentralised Aerial Swarm for Adaptive and Energy Efficient Transport of Unknown Loads

Kangyao Huang, Jingyu Chen, John Oyekan

Swarm and Evolutionary Computation (SWEVO) 2021 IF: 8.2



Projects


the Implementation of Flying Car for Ground-aerial Transportation

Partners: @School of Vehicle and Mobility, THU @Department of Computer Science and Technology, THU @Suzhou Automobile Research Institute-CN @Singapore University of Technology and Design @Bingo Intelligence Co., Ltd. @Fullymax Co., Ltd. @XY-UAV Co., Ltd. @RoboSense Co., Ltd.

Project Principal: Xinyu Zhang, Project Technical Leader: Kangyao Huang, Director: Jun Li

Other participants: Qihao Zhu, Qingjing Meng, Bo Cui, Songsong Rong, Haowen Shen, Guole Li, Huaping Liu, Jianxi Luo, Dafeng Jin, Jun Yang, Shuzhi Ge, Weiguo Yang, Yu Wan, Zhiqiang Yang, Zhenlong Ding, Xiaofeng Xu, Jiang Qian, Chaoyang Ha, Yuanhao Huang, Qiujiang Wu, Xingang Wu, Qifan Tan, Mo Zhou, Yang Shen, Li Wang, Yan Han, Zhaosheng Huang, Zhiwei Li, Lei Yang, Linxun Shi, Dazhong Xu, Kai Tang, et cetera.

We successfully developed the first generation of Tsinghua Mengshi intelligent flying car. This vehicle is the world first electric manned rotorcraft amphibious ground-aerial vehicle with integrated intelligent driving function.


Autonomous Driving Architecture towards SCSTSV

Director: Qifan Tan, Xinyu Zhang, Jun Li @New Technology Concept Vehicles, THU

Brief: Towards the Smart City-Smart Transportation-Smart Vehicles(SCSTSV), we focus on the key areas of autonomous driving technology, particularly in the design and optimization of architectures for perception, decision-making, and control. I propose a comprehensive architecture that integrates perception, decision-making, and control into a unified framework, further enhancing system performance through the integration of road testing equipment.


Solar-powered UAV for Long Duration Cruising

Work with Colleagues @Bingo Intelligence Co., Ltd.

Brief: This research focused on enhancing the endurance of solar-powered unmanned aerial vehicles (UAVs). A key aspect of the study involved redesigning the aerodynamic shape to improve efficiency. Additionally, our team developed a dynamic power system with low vortex drag variable-pitch propellers to adapt to varying wind speeds during flight, enabling them to operate efficiently across diverse conditions. This research contributes to the advancement of renewable energy-powered UAV technology, offering potential applications in various fields such as environmental monitoring, aerial photography, and telecommunications.

We honor the memory of Zhaoxi Wang, one of co-founders of the team, whose dedication and vision continue to inspire us as we move forward, and his spirit will forever remain an integral part of our journey,just like his aircraft did.


Auto-Patralling UAV Platform

Work with Colleagues @Bingo Intelligence Co., Ltd.

Brief: This project focused on the development of an autonomous inspection drone system for airports. This project encompassed the overall design of the airport system and the design and production of electromechanical controls. We prioritized the autonomous inspection functionality of the drones. Through a comprehensive approach balancing airport safety and efficiency, we devised a complete system including structural design of the drones, development of electromechanical control systems, and optimization of inspection algorithms. This system not only enables comprehensive inspection of airport facilities but also autonomously responds to and alerts to anomalies.


Oil-powered Variable-pitch Quadrotor

My dissertation for BEng degree. Notably, this is the first successful flight of oil-powered rotary-wing UAV utilizing variable-pitch control in China. We finished it at the end of 2015. Work with teammates Fanjie Kong, Jingdong Ma.

Brief: I participated a groundbreaking project focused on the development of a oil-powered variable-pitch multirotor unmanned aerial vehicle (UAV). This project involved the comprehensive design and prototyping testing of the UAV. Our efforts encompassed the integration of advanced variable-pitch technology with traditional oil-powered UAV systems, leading to a novel and efficient aerial platform. We use gears and belts as the power transmission method, where belts can effectively reduce the vibrations generated by the engine. The successful flight testing signifies a significant milestone in the domestic UAV industry, showcasing the feasibility and potential of variable-pitch control in enhancing the performance and versatility of oil-powered UAVs.


Education


 2022~now, 

PhD candidate in Computer Science and Technology, Tsinghua University, China

 Dissertation: 

Robot Interactive Learning

 2019~2020, 

MRes in Control & Systems Engneering, ACSE, the University of Sheffied, UK

 Dissertation: 

Cooperative Transport by Swarm Robots

 2012~2016, 

BEng in Aircraft Design, School of Astronautics, Northwestern Polytechnical University, China

 Dissertation: 

Oil-powered Quadrotor


Experiences


2015~2019, 

Co-Founder @Bingo Intelligence Co. Ltd., Xi'an, ShaanXi, China.

2020~2022, 

Research assistant @Institute for New Technology Concept Vehicles, THU, Beijing, China

2023~now, 

Founder @超微智导技术, China