Papers
4
Total Citations
42
H-Index
2
About
Zhitao Gao is a robotics researcher whose work lies at the intersection of intelligent skill learning and adaptive control for industrial manufacturing. His primary research focuses on developing force-relevant skill learning and generalization methods for robotic polishing and grinding—tasks that demand high precision and adaptability in uncertain environments. Gao’s most influential contribution is the AL-ProMP framework, which enables robots to learn and generalize complex force-based manipulation skills from human demonstrations, accumulating 21 citations since 2023. His 2022 work on intelligent learning models for strategy optimization in grinding and polishing has garnered 19 citations, further cementing his impact in the field. Beyond manufacturing, Gao has explored safety in human-robot interaction, proposing an intention-aware robust safety framework for teleoperation that unifies object interaction and obstacle avoidance using control barrier functions. This work addresses critical challenges in model uncertainties and adaptive safety boundaries. With a growing citation record and a clear trajectory toward bridging skill acquisition and operational safety, Zhitao Gao is emerging as a notable voice in the advancement of autonomous robotic manipulation for real-world contact tasks.
Research Focus
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Top Papers
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