In the present study, we propose a trajectory optimization and replanning algorithm for micro air vehicles (MAVs) in cluttered environments. To generate the path of an MAV in a cluttered environment, we first design an offline global path optimization algorithm. This algorithm generates a global trajectory for safe aerial delivery; this trajectory enables an MAV to avoid static obstacles marked in the navigation map and satisfies the MAV's initial and arrival velocities. The MAV's trajectory is replanned by exploiting dynamic movement primitives (DMPs) and a time adjustment algorithm to enable computationally efficient unknown obstacle avoidance in local path planning. To validate the applicability of the proposed algorithm, we compare simulation results with those obtained using an existing approach based on DMPs. Furthermore, an autonomous flight is demonstrated in an outdoor environment using a custom-made MAV driven by the proposed approach.
This article proposes an impact-time-control guidance law that can keep a non-maneuvering moving target in the seeker’s field of view (FOV). For a moving target, the missile calculates a predicted intercept point (PIP), designates the PIP as a new virtual stationary target, and flies to the PIP at the desired impact time. The main contribution of the article is that the guidance law is designed to always lock onto the moving target by adjusting the guidance gain. The guidance law for the purpose is based on the backstepping control technique and designed to regulate the defined impact time error. In this procedure, the desired look angle, which is a virtual control, is designed not to violate the FOV limit, and the actual look angle of the missile is kept within the FOV by tracking the desired look angle. To validate the performance of the guidance law, numerical simulation is conducted with different impact times. The result shows that the proposed guidance law intercepts the moving target at the desired impact time maintaining the target lock-on condition.
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