Estimation and Control of Noisy Riemannian Systems

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Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide: (i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise; (ii) New design methods that deal with noise in an optimal way; (iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems. The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.