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This paper concentrates on design of a vision-based guidance command for aerial manipulation of a cylindrical object, using a stochastic model predictive approach. We first develop an image-based cylinder detection algorithm that utilizes a geometric characteristic of perspectively projected circles in 3D space. To enforce the object to be located inside sight of a camera, we formulate a visual servoing problem as a stochastic model predictive control (MPC) framework. By regarding x and y axes rotational velocities as stochastic variables, we guarantee the visibility of the camera considering underactuation of the system. We also provide experimental results that validate effectiveness of the proposed algorithm.
Seo et al. (Mon,) studied this question.