Papers
2
Total Citations
8
H-Index
2
About
Xinpeng Di is a rising researcher in autonomous robotics and swarm intelligence, with a focus on bio-inspired control systems for complex capture and manipulation tasks. His work centers on developing intelligent motion planning and reinforcement learning algorithms for distributed robotic swarms and space robotic systems. Di’s most-cited paper, “Targets capture by distributed active swarms via bio-inspired reinforcement learning” (2024, 5 citations), introduces a novel framework that combines swarm dynamics with biologically inspired learning to enable coordinated target acquisition—a critical capability for applications like debris removal or search-and-rescue. His earlier study, “An Autonomous Motion Planning Method of a Dual-Arm Space Robotic System for Capturing Failed Satellites” (2023, 3 citations), addresses the challenge of autonomously grappling non-cooperative objects in orbit, proposing a dual-arm approach that enhances dexterity and safety. Though early in his career, Di’s contributions are already shaping the next generation of autonomous systems, bridging the gap between theoretical swarm algorithms and real-world robotic missions. His research holds promise for advancing space sustainability and multi-agent coordination.
Research Focus
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Top Papers
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