Top Open-source Projects
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.
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
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.
Selected Publications
Learning for Embodiment and Embodiment for Learning
Huaping Liu
Nature Reviews Electrical Engineering 2025
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
arXiv
Learning a Distributed Hierarchical Locomotion Controller for Embodied Cooperation
Chuye Hong*,
Kangyao Huang*,
Huaping Liu
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
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
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
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
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