Jingwei Cao

Papers

Total Citations

H-Index

About

Jingwei Cao is a robotics researcher whose work centers on bipedal locomotion, with a particular focus on achieving dynamic and robust running capabilities in legged robots. His most cited paper, "Simulation of Improved Bipedal Running Based on Swing Leg Control and Whole-body Dynamics" (2021), addresses a critical challenge in robotics: enabling precise, versatile, and real-time running motion. Cao’s major contribution lies in advancing the biologically inspired deadbeat (BID) controller, which traditionally allows for robust running but lacks fine position adjustment. By integrating swing leg control with whole-body dynamics, he enhances the controller’s ability to adapt to varied terrains and maintain stability, pushing the boundaries of athletic performance in humanoid robots. While his citation count (3) reflects a nascent stage of impact, this work is foundational for researchers exploring real-time, adaptive locomotion. Cao’s achievements underscore his role in bridging biological principles and robotic engineering, offering a pathway toward more agile, human-like machines. His research is particularly valuable for students and engineers aiming to develop robots capable of complex, dynamic movements in unstructured environments.