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Autonomous helicopter landing is a challenging task that requires preciseinformation about the aircraft states regarding the helicopters position,attitude, as well as position of the helipad. To this end, we propose asolution that fuses data from an Inertial Measurement Unit (IMU) and amonocular camera which is capable of detecting helipads position in the imageplane. The algorithm utilises manifold based nonlinear optimisation overpreintegrated IMU measurements and reprojection error in temporally uniformlydistributed keyframes, exhibiting good performance in terms of accuracy andbeing computationally feasible. Our contributions of this paper are the formaladdress of the landmarks Jacobian expressions and the adaptation of equalityconstrained Gauss-Newton method to this specific problem. Numerical simulationson MATLAB/Simulink confirm the validity of given claims.

State Estimation in Visual Inertial Autonomous Helicopter Landing Using Optimisation on Manifold