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This letter suggests an integrated approach for a drone (or multirotor) toperform an autonomous videography task in a 3-D obstacle environment byfollowing a moving object. The proposed system includes 1) a target motionprediction module which can be applied to dense environments and 2) ahierarchical chasing planner based on a proposed metric for visibility. In theprediction module, we minimize observation error given that the target objectitself does not collide with obstacles. The estimated future trajectory oftarget is obtained by covariant optimization. The other module, chasingplanner, is in a bi-level structure composed of preplanner and smooth planner.In the first phase, we leverage a graph-search method to preplan a chasingcorridor which incorporates safety and visibility of target during a timewindow. In the subsequent phase, we generate a smooth and dynamically feasiblepath within the corridor using quadratic programming (QP). We validate ourapproach with multiple complex scenarios and actual experiments. The sourcecode can be found in https://github.com/icsl-Jeon/traj_gen_vis

Integrated Motion Planner for Real-time Aerial Videography with a Drone in a Dense Environment