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Safe UAV navigation is challenging due to the complex environment structures,dynamic obstacles, and uncertainties from measurement noises and unpredictablemoving obstacle behaviors. Although plenty of recent works achieve safenavigation in complex static environments with sophisticated mappingalgorithms, such as occupancy map and ESDF map, these methods cannot reliablyhandle dynamic environments due to the mapping limitation from movingobstacles. To address the limitation, this paper proposes a trajectory planningframework to achieve safe navigation considering complex static environmentswith dynamic obstacles. To reliably handle dynamic obstacles, we divide theenvironment representation into static mapping and dynamic objectrepresentation, which can be obtained from computer vision methods. Ourframework first generates a static trajectory based on the proposed iterativecorridor shrinking algorithm. Then, reactive chance-constrained modelpredictive control with temporal goal tracking is applied to avoid dynamicobstacles with uncertainties. The simulation results in various environmentsdemonstrate the ability of our algorithm to navigate safely in complex staticenvironments with dynamic obstacles.

DPMPC-Planner: A real-time UAV trajectory planning framework for complex static environments with dynamic obstacles