Papers
11
Total Citations
337
H-Index
10
About
Albert Wu is a leading roboticist whose research focuses on dynamic locomotion, bipedal robotics, and control theory. His major contributions center on the application of the spring-mass model to achieve highly robust running and walking in uncertain environments. Wu’s work on deadbeat control policies—demonstrated on the ATRIAS bipedal robot—has shown how theoretical models can be translated into physical machines capable of withstanding large, unexpected disturbances. His most cited paper (84 citations) reveals a time-based deadbeat control for robust running, while his experimental evaluation of ATRIAS (38 citations) validates these theories in practice. Wu also advanced kinodynamic planning with the R3T algorithm (27 citations) and developed the Axel rover (15 citations) for planetary exploration in inaccessible terrains. His recent work on real-time model predictive control using differentiable simulation (10 citations) bridges simulation-to-reality transfer. With over 330 total citations, Wu’s research has profoundly influenced the design of compliant, agile robots that operate reliably in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Experimental Evaluation of Deadbeat Running on the ATRIAS Biped38 citations · 2017
- 4Robust spring mass model running for a physical bipedal robot29 citations · 2015
- 5
- 6Touch-down angle control for spring-mass walking27 citations · 2015
- 7
- 8Axel15 citations · 2009
- 9Highly robust running of articulated bipeds in unobserved terrain13 citations · 2014
- 10