Andrew Zheng

Papers

Total Citations

H-Index

About

Andrew Zheng is a roboticist advancing the frontier of safe autonomous navigation, with a focus on legged systems operating in complex, unstructured environments. His core research lies at the intersection of control theory and motion planning, where he has pioneered the use of **density functions** as a principled framework for safety-critical locomotion. Zheng’s most cited work, “Safe Navigation Using Density Functions” (9 citations), introduces an analytical method for constructing density functions that guarantee almost-everywhere safe navigation, moving beyond traditional barrier-function approaches. He extends this foundation to quadrupedal robots in “Safe Motion Planning for Quadruped Robots Using Density Functions” (4 citations), where he decomposes locomotion into a high-level density planner and a model predictive controller, enabling robust real-world deployment. Notably, his work on “Off-Road Navigation of Legged Robots Using Linear Transfer Operators” (2 citations) demonstrates how convex optimization and Perron-Frobenius operators can lift navigation problems into density space, allowing legged robots to traverse rugged terrain by leveraging traversability metrics. With a growing citation footprint, Zheng’s contributions are establishing density-based methods as a powerful alternative for certifiably safe motion planning in robotics.