Zhongxuan Cai
Papers
12
Total Citations
95
H-Index
5
About
Zhongxuan Cai is a leading researcher in multi-robot systems, behavior planning, and fault-tolerant cooperative robotics. His most influential work includes the development of "BT Expansion," a sound and complete algorithm for behavior planning using Behavior Trees (BTs), which has garnered 21 citations and revolutionized automated behavior synthesis for intelligent robots. Cai's ALLIANCE-ROS framework, with 19 citations, introduced a robust software architecture on ROS for fault-tolerant and cooperative mobile robots, enabling seamless multi-robot coordination and reusability. He has also made significant contributions to distributed control for flocking and group maneuvering of nonholonomic agents, and dynamic task allocation under communication constraints, each advancing practical applications in disaster rescue and UAV systems. Notable achievements include the Parallel Gym Gazebo platform, which accelerates deep reinforcement learning for robotics, and MRBTP for efficient multi-robot BT planning. With over 90 total citations across his top papers, Cai's work bridges theoretical algorithms and real-world robotic systems, offering scalable, resilient solutions for complex multi-agent environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6Subsumption model implemented on ROS for mobile robots5 citations · 2016
- 7
- 8MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaboration3 citations · 2025
- 9
- 10GSDF: A Generic Development Framework for Swarm Robotics2 citations · 2017