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Drone teleoperation is usually accomplished using remote radio controllers, devices that can be hard to master for inexperienced users. Moreover, the limited amount of information fed back to the user about the robots state, often limited to vision, can represent a bottleneck for operation in several conditions. In this work, we present a wearable interface for drone teleoperation and its evaluation through a user study. The two main features of the proposed system are a data glove to allow the user to control the drone trajectory by hand motion and a haptic system used to augment their awareness of the environment surrounding the robot. This interface can be employed for the operation of robotic systems in line of sight (LoS) by inexperienced operators and allows them to safely perform tasks common in inspection and search-and-rescue missions such as approaching walls and crossing narrow passages with limited visibility conditions. In addition to the design and implementation of the wearable interface, we performed a systematic study to assess the effectiveness of the system through three user studies (n = 36) to evaluate the users learning path and their ability to perform tasks with limited visibility. We validated our ideas in both a simulated and a real-world environment. Our results demonstrate that the proposed system can improve teleoperation performance in different cases compared to standard remote controllers, making it a viable alternative to standard Human-Robot Interfaces.
Teleoperation of robots enables remote intervention in distant and dangerous tasks without putting the operator in harms way. However, remote operation faces fundamental challenges due to limits in communication delay and bandwidth. The proposed work
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Complex tasks require human collaboration since robots do not have enough dexterity. However, robots are still used as instruments and not as collaborative systems. We are introducing a framework to ensure safety in a human-robot collaborative enviro