Pengyu Guo
Papers
2
Total Citations
2
H-Index
1
About
Pengyu Guo is an emerging researcher in aerospace engineering and intelligent control systems, with a primary focus on spacecraft guidance, pose estimation, and modular robotics for extreme space environments. His work bridges deep learning with classical control theory to address critical challenges in constrained space operations. In his 2024 study on quadrilateral pose estimation, Guo introduced a novel deep learning–based keypoint filtering method that significantly improves the accuracy and robustness of spacecraft pose determination—a fundamental requirement for autonomous rendezvous, docking, and debris removal. This work has already garnered attention for its potential to enhance real-time decision-making under the severe constraints of space. Building on this, his 2025 paper presents an innovative inner–outer loop computational framework for space modular robots, combining elite genetic algorithms with pursuit–evasion control to simultaneously optimize robot morphology and trajectory. This dual-layer approach represents a significant step toward adaptive, reconfigurable spacecraft systems. Though early in his career, Guo’s contributions are shaping the next generation of intelligent, autonomous space systems, demonstrating how machine learning can be practically integrated into safety-critical aerospace applications.
Research Focus
Key Achievements
Top Papers
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- 2