Junbao Gan
Papers
1
Total Citations
2
H-Index
1
About
Junbao Gan is a researcher whose work centers on advancing robotic teleoperation and manipulation systems, with a particular focus on enhancing dexterity and stability in complex tasks. His key research areas include multi-robot coordination, motion regulation, and human-robot interaction, where he explores how to optimize control strategies for challenging operations like flipping and grasping. Gan’s most notable contribution is his 2022 paper, “Motion Regulation for Single-Leader-Dual-Follower Teleoperation in Flipping Manipulation,” which introduces a novel framework for synchronizing a leader robot with two followers to achieve precise, stable flipping motions—a critical capability for applications in manufacturing, surgery, and hazardous environments. While this work has garnered 2 citations, its impact lies in laying foundational principles for scalable teleoperation systems that can handle dynamic, real-world tasks. Gan’s research bridges theory and practice, offering insights into motion planning and force feedback that are essential for next-generation robotic assistants. His achievements reflect a commitment to solving practical challenges in robotics, making his work a valuable resource for students and researchers interested in teleoperation, multi-agent systems, and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1