Papers
10
Total Citations
159
H-Index
5
About
Xianta Jiang is a leading researcher at the intersection of robotics, human-robot interaction, and tactile sensing, with a focus on enabling more intuitive and adaptive robotic manipulation. His work spans force myography (FMG) for continuous finger movement prediction—a technique with 61 citations that has opened new pathways for prosthetic control—and innovative solutions to the inverse kinematics problem for six-axis robots, a foundational challenge in robotics with 50 citations. Jiang has made significant contributions to tactile object recognition and pose estimation during grasping, using underactuated robotic hands and Bioin-Tacto sensor modules to overcome visual occlusion. His recent explorations into reinforcement learning for peg extraction and sensorless force estimation demonstrate a commitment to practical, real-world robotic dexterity. Notably, his systematic review of Furhat robots in education (2025) highlights his expanding interest in social robotics. With over 150 citations across his top ten papers, Jiang’s work is shaping how robots perceive, touch, and interact with their environments, making him a key figure in advancing both industrial and assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1Continuous Prediction of Finger Movements Using Force Myography61 citations · 2016
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