Yongqi Bi

Papers

Total Citations

H-Index

About

Yongqi Bi is a robotics researcher focused on advancing the capabilities of soft robotics through hybrid actuation and intelligent control systems. His primary research areas include hybrid-driven soft robots, pneumatic soft actuators, and the application of deep neural networks for robotic modeling. Bi’s major contribution lies in addressing the fundamental trade-off between the compliance of soft robots and the speed of rigid robots. His most cited work, "Design and experimental research of the hybrid-driven soft robot" (2023, 6 citations), introduces a novel system that combines motor-driven and pneumatic actuation to enable faster, more precise movement for detection tasks. This work is complemented by his 2024 paper on hybrid robot design for safe human-robot interaction in unknown environments. Notably, Bi’s 2025 paper pioneers the use of deep neural networks to model the nonlinear behavior of pneumatic soft actuators, overcoming a key challenge in soft robot control. With a growing citation record, Bi’s research is paving the way for practical, high-speed soft robotic systems that maintain safety and adaptability, making him a rising figure in the field of soft robotics and human-robot interaction.