Yixin Gu

The University of Texas at Arlington

Papers

6

Total Citations

100

H-Index

5

About

Yixin Gu is a robotics researcher whose work lies at the intersection of intelligent motion planning and soft robotic rehabilitation. Her primary research areas include reinforcement learning-based path planning for multi-robot systems and the development of soft pneumatic exoskeletons for upper-limb rehabilitation. Gu’s major contribution in path planning is her pioneering use of integral reinforcement learning (IRL) to solve the minimum time-energy path planning problem in unknown, disturbance-prone environments—a critical advancement for energy-constrained autonomous robots. Her most cited paper (40 citations) applies IRL to multi-robot collision avoidance under environmental uncertainty, while a related work (15 citations) formalizes the approximate minimum time-energy approach. In rehabilitation robotics, Gu has developed a pneumatically actuated soft robotic hand and wrist exoskeleton (25 citations), a bilateral rehabilitation system for hand and wrist joints, and an assistive glove integrated with immersive virtual reality games to boost patient motivation. Her work bridges theoretical control algorithms with practical, compliant hardware, aiming to restore fine motor function in post-stroke patients. With growing impact across both autonomous systems and assistive technology, Gu’s research exemplifies a commitment to safe, efficient, and human-centered robotics.

Research Focus

Key Achievements

5
H-Index
6
Papers
100
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Integral Reinforcement Learning-Based Multi-Robot Minimum Time-Energy Path Planning Subject to Collision Avoidance and Unknown Environmental Disturbances
40 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: The University of Texas at Arlington

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago