Jinze Liu
Papers
2
Total Citations
17
H-Index
2
About
Jinze Liu is a robotics researcher whose work centers on the real-time safety and navigation of bipedal robots, with a particular focus on obstacle avoidance and locomotion control. His major contributions lie in the integration of Control Lyapunov Functions (CLF) and Control Barrier Functions (CBF) to create reactive planning systems that enable bipedal robots, such as the Cassie-series, to dynamically avoid multiple obstacles in complex environments. Liu’s 2023 paper, "CLF-CBF Constraints for Real-Time Avoidance of Multiple Obstacles in Bipedal Locomotion and Navigation," has garnered 12 citations, showcasing its impact on the field. This work introduces a continuously differentiable CBF that processes LiDAR-derived height maps for real-time obstacle detection and avoidance, a significant advancement for safe bipedal navigation. Another notable paper, "Realtime Safety Control for Bipedal Robots to Avoid Multiple Obstacles Via Clf-Cbf Constraints" (2023, 5 citations), further solidifies his expertise in safety-critical control. Liu’s research is pivotal for advancing autonomous bipedal robots in cluttered, real-world settings, making him a key figure in the intersection of control theory and robotics.
Research Focus
Key Achievements
Top Papers
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- 2