Abstract
In this paper we investigate the problem of autonomously tracking a ground moving target in an urban area by unmanned aerial vehicles (UAVs). In this scenario, the target is tracked by two UAVs with on-board sensors under the constraints of urban area occlusions. Information regarding the line of sight occlusions in the urban area is available from a database. To ensure successfully trajectory planning, the UAVs' dynamic constrains must be taken into account. Model predictive control(MPC) method is introduced for a cooperative motion planning in real time. To test the MPC algorithm, simulations using a visual database of the CBD in Singapore are conducted and the performance is showed in three different scenarios.
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