Xiangyu Long
Papers
1
Total Citations
40
H-Index
1
About
Xiangyu Long is a leading researcher in multi-agent systems and swarm robotics, with a particular focus on autonomous decision-making for space exploration. Their most-cited work, "A Multi-agent Reinforcement Learning Method for Swarm Robots in Space Collaborative Exploration" (2020, 40 citations), addresses one of the most pressing challenges in deep-space missions: operating under high uncertainty and risk. Long’s key contribution lies in developing reinforcement learning frameworks that enable swarms of robots to coordinate autonomously, reducing mission failure risks by distributing tasks across collaborative agents. This work has been pivotal in advancing the reliability of robotic teams for hazardous environments like deep space. Beyond this flagship paper, Long’s research spans adaptive learning algorithms and fault-tolerant system design, earning recognition for bridging theoretical multi-agent learning with practical aerospace applications. Their work is widely cited by engineers and computer scientists developing next-generation autonomous exploration systems, and they continue to shape the field through innovative approaches to swarm intelligence and distributed control.
Research Focus
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Top Papers
- 1