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1.
Front Robot AI ; 6: 95, 2019.
Article in English | MEDLINE | ID: mdl-33501110

ABSTRACT

Exploration of challenging indoor environments is a demanding task. While automation with aerial robots seems a promising solution, fully autonomous systems still struggle with high-level cognitive tasks and intuitive decision making. To facilitate automation, we introduce a novel teleoperation system with an aerial telerobot that is capable of handling all demanding low-level tasks. Motivated by the typical structure of indoor environments, the system creates an interactive scene topology in real-time that reduces scene details and supports affordances. Thus, difficult high-level tasks can be effectively supervised by a human operator. To elaborate on the effectiveness of our system during a real-world exploration mission, we conducted a user study. Despite being limited by real-world constraints, results indicate that our system better supports operators with indoor exploration, compared to a baseline system with traditional joystick control.

2.
IEEE Trans Vis Comput Graph ; 24(4): 1437-1446, 2018 04.
Article in English | MEDLINE | ID: mdl-29543162

ABSTRACT

Drones allow exploring dangerous or impassable areas safely from a distant point of view. However, flight control from an egocentric view in narrow or constrained environments can be challenging. Arguably, an exocentric view would afford a better overview and, thus, more intuitive flight control of the drone. Unfortunately, such an exocentric view is unavailable when exploring indoor environments. This paper investigates the potential of drone-augmented human vision, i.e., of exploring the environment and controlling the drone indirectly from an exocentric viewpoint. If used with a see-through display, this approach can simulate X-ray vision to provide a natural view into an otherwise occluded environment. The user's view is synthesized from a three-dimensional reconstruction of the indoor environment using image-based rendering. This user interface is designed to reduce the cognitive load of the drone's flight control. The user can concentrate on the exploration of the inaccessible space, while flight control is largely delegated to the drone's autopilot system. We assess our system with a first experiment showing how drone-augmented human vision supports spatial understanding and improves natural interaction with the drone.


Subject(s)
Aircraft , Computer Graphics , Data Display , Imaging, Three-Dimensional/methods , Man-Machine Systems , Adult , Humans , Male , Video Recording , Virtual Reality , X-Rays , Young Adult
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