In this paper, we present a coordinated and reactive human-aware motion planner for performing a handover task by an autonomous aerial manipulator (AAM). We present a method to determine the final state of the AAM for a handover task based on the current state of the human and the surrounding obstacles. We consider the visual field of the human and the effort to turn the head and see the AAM as well as the discomfort caused to the human. We apply these social constraints together with the kinematic constraints of the AAM to determine its coordinated motion along the trajectory.
The use of drones in human-populated areas is increasing day by day. Such robots flying in close proximity to humans and potentially interacting with them, as in object handover or delivery, need to carefully plan their navigation considering the presence of humans. We propose a humanaware 3D reactive planner based on stochastic optimization for drone navigation. Besides considering the kinematics constraints of the drone, we propose two criteria to produce socially acceptable trajectories. The first, called discomfort, considers the unease caused to the humans spatially close to fast-moving drones. The second, called visibility, promotes the drone's visibility for humans. We demonstrate the planner's performance and adaptability in various simulated experiments.
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