Sort by
Refine Your Search
-
neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform
-
terrain, the co-evolution of morphology and control for soft and legged robots using differentiable and evolutionary optimisation, and gravity-aware locomotion strategies for mass- and energy-limited
-
particular its applied mathematics and advanced numerics, as well as the team’s other main research lines (for example AI for guidance, navigation and control, unconventional computing and fundamental physics
Searches related to robust control
Enter an email to receive alerts for robust-control positions