David Wang

University of California, Berkeley, University of Waterloo, UES (United States)

Papers

Total Citations

223

H-Index

About

David Wang is a pioneering roboticist whose research spans mechanical search, control theory, and flexible manipulators. His landmark 2019 work on "Mechanical Search" (108 citations) introduced a formal framework for robots to retrieve target objects from cluttered, unstructured environments—a critical capability for warehouse automation, home robotics, and retail applications. Earlier, Wang made foundational contributions to control systems with his 2012 paper on path following for mechanical systems (62 citations), which developed controllers enabling robots to traverse paths without predefined timing—essential for autonomous navigation. His 1995 work on closed-loop shaped-input strategies (37 citations) addressed vibration suppression in flexible-link robots, a key challenge in precision manufacturing. Wang's research demonstrates remarkable breadth, from theoretical control design to practical manipulation in clutter. His work on passive controllers for flexible manipulators (1997) further advanced the field of compliant robotics. With over 220 total citations across his most influential papers, Wang's contributions continue to shape how robots interact with and navigate through complex, real-world environments.