Xia Peng
Papers
2
Total Citations
5
H-Index
2
About
Xia Peng’s research focuses on advancing autonomous navigation and adaptive control for robotic systems, particularly in unstructured and unknown environments. Her work bridges critical gaps in mobile robot path planning and manipulator control by developing algorithms that operate without pre-existing kinematic or environmental models. In her highly cited 2011 paper, Peng introduced a multi-constrained local environment modeling method for mobile robot path planning, integrating traversability, security, movement smoothness, and goal-guiding constraints to optimize overall path performance—a foundational contribution to adaptive window approaches. Her 2013 work further extends this adaptability by proposing a dynamic Jacobian identification method using state-space models and Kalman filtering for visual servoing, enabling robot manipulators to function without calibrated cameras or known kinematics. Though her citation counts reflect a focused, emerging impact (3 and 2 citations respectively), these papers represent early, principled steps toward robust, model-independent robotics. Peng’s contributions are particularly notable for their practical emphasis on real-world deployment, offering solutions that reduce reliance on precise modeling—a key challenge in field robotics. Her work continues to inspire researchers tackling sensorimotor control in dynamic, unstructured settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2