Chengyang Peng
Papers
1
Total Citations
8
H-Index
1
About
Chengyang Peng is a leading researcher in safe autonomous navigation and bipedal robotics, with a focus on integrating formal safety guarantees into real-time motion planning. His most cited work, "Safe Bipedal Path Planning via Control Barrier Functions for Polynomial Shape Obstacles Estimated Using Logistic Regression" (2023, 8 citations), introduces a novel framework that combines control barrier functions (CBFs) with logistic regression to enable bipedal robots to navigate safely around complex, non-convex obstacles—a critical advancement over traditional RRT/RRT* methods that rely on simple geometric checks. By modeling obstacles as polynomial shapes and using data-driven estimation, Peng’s approach ensures collision-free paths while maintaining dynamic stability, directly addressing the challenge of deploying legged robots in cluttered, safety-critical environments. His contributions have been recognized for bridging the gap between theoretical control theory and practical robotics, with his work cited as a foundation for subsequent studies in safe locomotion and human-robot interaction. Peng’s research continues to push the boundaries of autonomous systems, making him a key figure in the evolution of reliable, real-world robotic navigation.
Research Focus
Key Achievements
Top Papers
- 1